72236 2012 Information and Communications for Development Maximizing Mobile 2012 Information and Communications for Development 2012 Information and Communications for Development Maximizing Mobile © 2012 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved 1 2 3 4 15 14 13 12 This work is a product of the staff of The World Bank with external contributions. Note that The World Bank does not necessarily own each component of the content included in the work. The World Bank therefore does not warrant that the use of the content contained in the work will not infringe on the rights of third parties. The risk of claims resulting from such infringement rests solely with you. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guaran- tee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be considered to be a limitation upon or waiver of the privileges and immuni- ties of The World Bank, all of which are specifically reserved. Rights and Permissions This work is available under the Creative Commons Attribution 3.0 Unported license (CC BY 3.0) http://creativecommons.org/licenses/by/3.0. Under the Creative Commons Attribution license, you are free to copy, distribute, transmit, and adapt this work, including for commercial purposes, under the following conditions: Attribution—Please cite the work as follows: World Bank. 2012. Information and Communications for Development 2012: Maximizing Mobile. Washington, DC: World Bank. DOI: 10.1596/978-0-8213-8991-1; website: http://www .worldbank.org/ict/IC4D2012. License: Creative Commons Attribution CC BY 3.0 Translations—If you create a translation of this work, please add the following disclaimer along with the attribution: This translation was not created by The World Bank and should not be considered an official World Bank translation. The World Bank shall not be liable for any content or error in this translation. All queries on rights and licenses should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@worldbank.org. ISBN (paper): 978-0-8213-8991-1 ISBN (electronic): 978-0-8213-9587-5 DOI: 10.1596/978-0-8213-8991-1 Cover photographs: Top and bottom: G. M. B. Akash / Panos; center: Mr. Pierre C. Sibiry Traore, ICRISAT, AgCom- mons, a program executed by the Consultative Group on International Agricultural Research (CGIAR); right: The Commonwealth of Learning Cover design: Naylor Design Table of Contents Foreword xi Preface xiii Acknowledgments xv Abbreviations xvii PART I Executive Summary 3 Tim Kelly and Michael Minges Main messages 3 Why are mobile phones now considered indispensable? 4 A mobile green revolution 5 Keep using the tablets—how mobile devices are changing health care 5 Mobile money 6 Get a phone, get a job, start a business 6 Using phones to bring governments and citizens closer 6 Onward and upward to mobile broadband 7 Appendixes 7 Infographic: Maximizing Mobile for Development 8 Chapter 1 Overview 11 Michael Minges How mobile phones are used 13 Data traffic 18 The changing mobile ecosystem 19 Mobile-enabled social and economic trends 22 Structure of the report 27 Notes 27 References 28 v Chapter 2 Mobilizing the Agricultural Value Chain 31 Naomi J. Halewood and Priya Surya Making information mobile 31 Improved access to agricultural information 33 Improving data visibility for value-chain efficiency 37 Enhancing access to markets 39 Policy considerations 41 Conclusions 41 Notes 42 References 42 Chapter 3 mHealth 45 Nicolas Friederici, Carol Hullin, and Masatake Yamamichi Why mHealth? Opportunities and challenges 45 The potential of mHealth 50 The mHealth ecosystem 52 Business models for mHealth 52 Principles for implementing mHealth applications 53 Conclusions 57 Notes 58 References 58 Chapter 4 Mobile Money for Financial Inclusion 61 Kevin Donovan Mobile money: an ecosystem approach 61 The financial inclusion imperative 62 What is the impact of mobile money? 63 Growing mobile money: challenges and success stories 65 Emerging issues in mobile money 66 Conclusions 71 Notes 72 References 72 Chapter 5 Mobile Entrepreneurship and Employment 75 Maja Andjelkovic and Saori Imaizumi Open innovation and mobile entrepreneurship 76 Mobile incubators 79 Mobile microwork 81 Mobiles and recruitment 82 Conclusions and considerations for policy-makers 83 Notes 85 References 86 vi Contents Chapter 6 Making Government Mobile 87 Siddhartha Raja and Samia Melhem with Matthew Cruse, Joshua Goldstein, Katherine Maher, Michael Minges, and Priya Surya A typology of mGovernment 87 Drivers for mGovernment 89 Challenges for governments 93 Enabling the technology transformation 94 Emerging best practices for going mobile 95 Conclusions 98 Notes 99 References 100 Chapter 7 Policies for Mobile Broadband 103 Victor Mulas The mobile broadband opportunity and developing countries 103 Policy recommendations for facilitating mobile broadband diffusion 104 Conclusions 110 Notes 110 References 111 PART II Key Trends in the Development of the Mobile Sector 115 Michael Minges Access 115 Mobile broadband 120 Devices 121 Mobile industry 124 A mobile analytical tool 126 Notes 133 References 134 Data Notes 135 Kaoru Kimura and Michael Minges Definitions and data sources 138 Mobile at-a-glance country tables 141 Key mobile indicators for other economies, 2010 217 Contributors 219 BOXES Part I 1.1 Mobile phones and applications 14 1.2 How to make a million from Angry Birds 19 Contents vii 1.3 Smartphones and tablets for development 24 2.1 How Reuters Market Light generates hyperlocalized information 35 2.2 A pregnant pause for Sri Lanka’s cows 36 2.3 Tracking specialty coffee 38 2.4 DrumNet, the value chain on your mobile phone 39 3.1 Kenya: A breeding ground for mHealth applications 48 3.2 Ethiopia: SMS helps in monitoring UNICEF’s food supply chain 49 3.3 India: Health Management and Research Institute—104 Mobile 56 4.1 One device, many channels 62 4.2 Using mobile money 64 4.3 Business models for mobile money 67 4.4 Interoperability and innovation in mobile money 70 5.1 AkiraChix 78 5.2 infoDev’s mLabs and mHubs 80 5.3 Mobile microwork: JANA 82 5.4 Turning ideas into applications: “Mobile To Work� challenge 83 5.5 Business processes for job seekers and employers: Souktel’s JobMatch 84 6.1 The mobile telephone as a tool for citizen voice and empowerment 90 6.2 Kerala’s mobile government program 93 6.3 Evolving toward coordination: the case of the Republic of Korea 94 6.4 Open data and mobile access in Kenya 97 6.5 Challenges to trust and credibility 99 7.1 Using reverse auctions to match spectrum allocations with coverage obligations in Chile 107 Part II A.1 Mobile use in rural China 118 FIGURES Part I 1.1 The developing world: young and mobile 12 1.2 Talking and paying: mobile voice use and price for selected countries, 2010 14 1.3 Mobile phone usage around the world, 2011 16 1.4 Worldwide SMS and Twitter traffic 17 1.5 Data, data everywhere 20 1.6 Apples and Berries: iPhone sales and Blackberry subscriptions 20 1.7 Changing market share of mobile handset sales by operating system 21 1.3.1 Annotated screenshot of Bangladesh’s Amadeyr Tablet 24 1.8 Mapping calls for protest on Facebook to actual “Arab Spring� demonstrations, 2011 26 1.9 Mobile phone versus internet access household availability 27 3.1.1 MedAfrica app 48 3.2.1 RapidSMS in Ethiopia 49 3.1 Relative popularity of consumer health applications in Apple’s App Store, 2011 51 viii Contents 3.2 Number of countries with at least one mHealth deployment, by World Bank region 52 3.3 mHealth ecosystem 52 4.1 Different types of mobile financial services 62 4.2 Global mobile money deployments 63 4.3.1 Mobile money demand curves 67 4.3 The most and least expensive remittance corridors 69 5.1 Rewards and risks from entrepreneur participation in social networks 79 5.2 infoDev’s network of mLabs 80 6.1.1 Screenshot of the original Ushahidi mash-up 90 6.4.1 Screenshot from Open Data Kenya website, showing poverty and pupils per teacher 97 7.1 Broadband subscriptions in selected countries per platform (mobile vs. fixed) 104 7.2 Broadband as an ecosystem where supply and demand factors interact with each other 104 7.1.1 Mobile broadband subscriptions per operator in Chile 107 7.3 Mobile data traffic by 2016, CISCO forecast 108 7.4 Mobile applications as a driver of mobile broadband demand 110 Part II A.1 Worldwide fixed and mobile telephone subscriptions 116 A.2 Mobile cellular subscriptions per 100 people, by income group 116 A.3 Mobile household penetration, Senegal and other selected countries, 2009 117 A.1.1 Mobile usage in rural areas of three Chinese provinces, 2011 118 A.4 Population, mobile subscriptions, and poverty headcount in low- and middle-income economies 119 A.5 Affordability and coverage in developing economies 119 A.6 Mobile broadband 120 A.7 Broadband subscriptions in the Philippines and South Africa 121 A.8 Global sales of mobile and computing devices 123 A.9 Smartphone penetration as a share of population, 2011 124 A.10 Global telecommunication services market 124 A.11 Mobile value chain 125 A.12 Mobile analytical tool: indicators and categories 127 A.13 Mobile analytical tool scores, 2005 and 2010, by income and region group 131 A.14 Mobile analytical tool and GNI per capita, 2010 131 A.15 Mobile analytical tool: China and Sri Lanka compared 132 A.16 Mobile analytical tool components summarized 133 TABLES Part I 1.1.1 Mobile devices and their capabilities 15 1.1 Top mobile applications, June 2011 18 1.2 Mobile and the Millennium Development Goals 23 Contents ix 2.1 Mobile-enabled solutions for food and agriculture 32 2.2 Impact of ICT on farmers, traders, and consumers 34 3.1 Major categories of mHealth services and applications 46 3.2 Selected examples of mHealth projects and lessons learned 54 6.1 Three types of mGovernment 88 6.2 Policies and programs to promote mGovernment 95 Part II A.1 Mobile data speeds and volumes, Q3 2011 122 A.2 Private participation in mobile networks, 1990–2010 126 A.3 Worked example of the mobile analytical tool, Morocco 128 A.4 Mobile analytical tool components for 100 selected economies, 2005 and 2010 128 x Contents Foreword Mobile phones, a rarity in many developing countries at the is available in the Little Data Book on Information and turn of the century, now seem to be everywhere. Between Communication Technology 2012, published alongside this 2000 and 2012, the number of mobile phones in use world- report. wide grew from fewer than 1 billion to around 6 billion. The It is our hope that this new report will provide some mobile revolution is transforming livelihoods, helping to emerging good-practice principles for policy-makers, regu- create new businesses, and changing the way we communi- lators, and investors in this complex and constantly chang- cate. The mobile phone network is already the biggest ing sector. The World Bank Group already supports a wide “machine� the world has ever seen, and now that machine is range of investment lending programs with an ICT compo- being used to deliver development opportunities on a scale nent. According to the report of the Independent Evaluation never before imagined. During this second decade of the Group, Capturing Technology for Development (2011), new millennium, maximizing the potential of mobile around three-quarters of all investment lending projects phones is a challenge that will engage governments, the from the World Bank Group have an ICT component; in private sector, and the development community alike. addition, more than $4 billion has been invested directly in Information and Communications for Development the ICT sector between 2003 and 2010. 2012: Maximizing Mobile is the third report in the World This report marks a shift from the World Bank Group’s Bank Group’s series on Information and Communication traditional focus on ICT connectivity to a new focus on Technologies (ICTs) for Development, originally applications and on the ways ICTs, especially mobile launched in 2006. This edition focuses on mobile applica- phones, are being used to transform different sectors of the tions and their use in promoting development, especially global economy. This change of focus reflects how the in agriculture, health, financial services, and government. value created by the industry is shifting from networks and Cross-cutting chapters present an overview of emerging hardware to software and services. The World Bank Group trends in mobile applications, the ways they are affecting expects that the theme of transformation will increasingly employment and entrepreneurship opportunities, and the guide its investment lending, and this report is aligned with policy challenges presented by the ongoing shift from that new direction. Ultimately, the mission of the World narrowband to broadband mobile networks. The report Bank is to work for a world free of poverty—a goal that is features at-a-glance tables for 152 economies showing the likely to be achieved more efficiently when ICT investment latest available data and indicators for the mobile sector is integrated effectively alongside investment in sectors (year-end 2011, where possible). The report also intro- such as agriculture, health, and government. duces an analytical tool for examining the relevant performance indicators for each country’s mobile sector, Marianne Fay so policy-makers can assess their capacities relative to Chief Economist, Sustainable Development Network other countries. A more complete range of ICT indicators The World Bank xi Preface The World Bank’s new strategy for engagement in the Infor- phones are upgraded to smartphones and tablets. The full mation and Communication Technologies (ICTs) sector, range of innovative mobile applications described in this which comes into force in 2012, is built around three strate- report is not yet available in all countries and to all gic themes: Innovate—ICT for innovation and ICT-based subscribers, but it soon will be. And the expectation is services industries; Connect—affordable access to voice, high- that developing countries will invent and adapt their own speed internet, information and media; and Transform—ICT mobile applications, suited to local circumstances and applications to transform services for enhanced development needs. For that reason more research is needed on how outcomes. mobile applications are used in base of the pyramid This new flagship report on Information and Communi- households. cations for Development builds on these three themes. In This report, like its predecessors, was researched and particular, the report shows how innovation in the manu- written jointly by the ICT Sector Unit and by infoDev, a facture of mobile handsets—giving them more memory, global partnership program of the World Bank Group. It faster processing power, and easier-to-use touchscreen has been reviewed by a broad range of experts working in interfaces—married with higher performance and more the field, both within and outside the Bank, whose contri- affordable broadband networks and services produces trans- butions are gratefully acknowledged. Funding is provided formation throughout economies and societies. Increas- by the World Bank as well as infoDev’s donors, notably the ingly, that transformation is coming from developing Ministry for Foreign Affairs of the Government of countries, which are “more mobile� than developed coun- Finland, the Korean Trust Fund for ICT4D, and UKaid. tries in the sense that they are following a “mobile first� The World Bank Group is committed to continuing its development trajectory. Many mobile innovations (includ- analytical and lending operations to support progress and ing multi-SIM card phones, low-cost recharges, and mobile the sharing of best practices and knowledge, as well as payments) increasingly originate in poorer countries and expanding its investments in private ICT companies to spread from there. further growth in the sector, competitiveness, and the Since the last Information and Communications for availability of better-quality, affordable ICT services to all Development report was published, almost 2 billion new the world’s inhabitants. mobile phone subscriptions have been added worldwide, Juan Navas-Sabater and the majority of these are in the developing world. Acting Sector Manager, ICT Sector Unit This rapid growth does not show the whole picture, The World Bank however. Alongside the process of enlarging the network is an equally important process of improving the quality Valerie D’Costa and depth of the network as narrowband networks are Program Manager, infoDev upgraded to broadband and as basic phones and feature- The World Bank xiii Acknowledgments This report was prepared by a team from the ICT Sector The principal authors of Part II were Michael Minges Unit (TWICT), infoDev, and the Development Economics and Kaoru Kimura, and the editorial team for the statistical Data Group (DECDG) of the World Bank Group. The edito- tables comprised Neil Fantom, Buyant Erdene Khaltarkhuu, rial team was led by Tim Kelly and comprised Nicolas Kaoru Kimura, Soong Sup Lee, Michael Minges, and Friederici, Michael Minges, and Masatake Yamamichi. Their William Prince. work was overseen by a peer-review team, led by Marianne Inputs, comments, guidance, and support at various Fay, that included Jose Luis Irigoyen, Valerie D’Costa, stages of the report’s preparation were received from the Philippe Dongier, Phillippa Biggs (ITU), and Christine following World Bank Group colleagues: Maria Amelina, Zhenwei Qiang. Edward Anderson, Elizabeth J. Ashbourne, Seth Ayers, Alan The principal authors of the chapters in Part I of the Carroll, Vikas Choudhary, Toni Eliasz, Tina George, Joshua report are: Goldstein, Aparajita Goyal, Siou Chew Kuek, Katherine Maher, Wonki Min, Fernando Montenegro Torres, Arata • Tim Kelly and Michael Minges (Executive Summary) Onoguchi, Tiago Peixoto, Mark Pickens, Carlo Maria • Michael Minges (Chapter 1) Rossotto, Leila Search, and Randeep Sudan, as well as from the principal authors. • Naomi J. Halewood and Priya Surya (Chapter 2) External reviewers, to whom special thanks are owed, • Nicolas Friederici, Carol Hullin, and Masatake included Phillippa Biggs (ITU), Steve Esselaar (Intelecon), Yamamichi (Chapter 3) Shaun Ferris (Catholic Relief Services), Vicky Hausmann (Dalberg), Janet Hernandez (Telecommunications Manage- • Kevin Donovan (Chapter 4) ment Group), Jake Kendall (Gates Foundation), Vili • Maja Andjelkovic and Saori Imaizumi (Chapter 5) Lehdonvirta (London School of Economics), Daniel Leza (Telecommunications Management Group), Bill Maurer • Siddhartha Raja and Samia Melhem, with Matthew (University of California, Irvine), Sascha Meinrath (New Cruse, Joshua Goldstein, Katherine Maher, Michael America Foundation), Marcha Neethling (Praekelt Founda- Minges, and Priya Surya (Chapter 6) tion), Brooke Partridge (Vital Wave Consulting), Ganesh • Victor Mulas (Chapter 7) Ramanathan (Tiger Party), Michael Riggs (Food and xv Agriculture Organization), Stephen Rudgard (Food and Agri- • The Ministry for Foreign Affairs of the Government of culture Organization), Brendan Smith (Vital Wave Consult- Finland for its support for the Finland / infoDev / Nokia ing), Scott Stefanski (Bazaar Strategies), Heather Thorne program on Creating Sustainable Businesses in the Knowl- (Grameen Foundation), Katrin Verclas (Mobile Active), and edge Economy, which supported the production of the Anthony Youngblood (New America Foundation). report as well as research for chapters 1, 2, 4, and 5. Special thanks are owed to Phillippa Biggs (ITU), who • The Korean Trust Fund (KTF) on Information and provided a thorough and dedicated peer review of all chap- Communication Technology for Development (ICT4D), ters, as well as to Denis Largeron and Marta Priftis from which supported background research for chapters 2, 3, TWICT, and to Denise Bergeron, Jose De Buerba, Aziz 4, and 5. Gökdemir, Stephen McGroarty, and Santiago Pombo- Bejarano, from the World Bank Office of the Publisher for • UKaid, which supported background research for chapter oversight of the editorial production, design, printing, and 7 through its support for infoDev’s analytical work dissemination of the book. The infographic in the Executive program. Summary was prepared by Zack Brisson and Mollie Ruskin of Reboot (www.thereboot.org), with guidance from the The team would also like to thank the many other indi- editorial team. viduals, firms, and organizations that have contributed A report of this nature would be impossible without the through their continuing support and guidance to the work support of our development partners. For this edition of the of the World Bank Group over the three years since the last report, special thanks are due to: report in this series was published. xvi Acknowledgments Abbreviations 2G second generation (mobile GPS Global Positioning System communications) GSM Global System for Mobile 3G third generation (mobile communications communications) GTUGS Google Technology User Groups 4G fourth generation (mobile HSPA High-Speed Packet Access (cellular communications) mobile standard) apps applications HTML hypertext mark-up language ATM automated teller machine IC4D Information and Communications CDMA Code Division Multiple Access for Development (cellular mobile standard) ICT information and communication CGAP Consultative Group to Assist the Poor technology IM instant messaging e-payment electronic payment IMF International Monetary Fund e-services electronic services ISP internet service provider ebook electronic book ITU International Telecommunication eCommerce electronic commerce Union EDGE Enhanced Data Rates for GSM Evolution (cellular mobile kbit/s kilobits per second standard) LTE Long Term Evolution (cellular mobile eGovernment electronic government standard) eHealth electronic health EV-DO Evolution–Data Optimized (cellular MB megabyte mobile standard) Mbit/s Megabits per second MDGs Millennium Development Goals GB gigabyte mGovernment mobile government GDP gross domestic product mHealth mobile health GNI gross national income mLab mobile applications laboratory xvii NFC near field communications UNCTAD United Nations Conference on Trade NGO nongovernmental organization and Development UNDP United Nations Development OECD Organisation for Economic Programme Co-operation and Development UNESCO United Nations Educational, Scientific PC personal computer and Cultural Organization PDA personal digital assistant UNICEF United Nations Children's Fund PPP public-private partnership USB universal serial bus USSD Unstructured Supplementary RFID radio frequency identification Service Data SAR special autonomous region SIM subscriber identity module W-CDMA Wideband Code Division SME small and medium enterprise Multiple Access (cellular SMS short message service mobile standard) WHO World Health Organization TCO total cost of ownership WiMAX Worldwide Interoperability for TD-SCDMA Time Division Synchronous Code Microwave Access (wireless standard) Division Multiple Access (cellular mobile standard) All dollar amounts are U.S. dollars unless otherwise indicated. xviii Abbreviations Part I Executive Summary Tim Kelly and Michael Minges Main messages Mobile applications not only empower individual users, they enrich their lifestyles and livelihoods, and boost the ith some 6 billion mobile subscriptions in W use worldwide, around three-quarters of the world’s inhabitants now have access to a mobile phone. Mobiles are arguably the most ubiquitous economy as a whole. Indeed, mobile applications now make phones immensely powerful as portals to the online world. A new wave of “apps,� or smartphone applications, and “mash- ups� of services, driven by high-speed networks, social modern technology: in some developing countries, more networking, online crowdsourcing, and innovation, is help- people have access to a mobile phone than to a bank ing mobile phones transform the lives of people in developed account, electricity, or even clean water. Mobile communica- and developing countries alike. The report finds that mobile tions now offer major opportunities to advance human applications not only empower individuals but have impor- development—from providing basic access to education or tant cascade effects stimulating growth, entrepreneurship, health information to making cash payments to stimulating and productivity throughout the economy as a whole. Mobile citizen involvement in democratic processes. communications promise to do more than just give the The developing world is “more mobile� than the devel- developing world a voice. By unlocking the genie in the oped world. In the developed world, mobile communica- phone, they empower people to make their own choices and tions have added value to legacy communication systems decisions. and have supplemented and expanded existing information Near ubiquity brings new opportunities. This 2012 flows. However, the developing world is following a differ- edition of the World Bank’s Information and Communica- ent, “mobile first� development trajectory. Many mobile tions for Development report analyzes the growth and evolu- innovations—such as multi-SIM card phones, low-value tion of mobile telephony, and the rise of data-based services recharges, and mobile payments—have originated in poorer delivered to handheld devices, including apps. The report countries and are spreading from there. New mobile appli- explores the consequences for development of the emerging cations that are designed locally and rooted in the realities of “app economy.� It summarizes current thinking and seeks to the developing world will be much better suited to address- inform the debate on the use of mobile phones for develop- ing development challenges than applications transplanted ment. This report looks at key ecosystem-based applications from elsewhere. In particular, locally developed applications in agriculture, health, financial services, employment, and can address developing-country concerns such as digital government, with chapters devoted to each. The story is no literacy and affordability. 3 longer about the phone itself, but about how it is used, and Why are mobile phones now consid- the content and applications to which mobile phones ered indispensable? provide access. The report’s opening chapter provides an overview of the Engaging mobile applications for development key trends shaping and transforming the mobile industry as requires an enabling “ecosystem.� Apps are software well as their impact on development. The chapter examines “kernels� that sit on a mobile device (typically a smartphone the evolution of the mobile phone from a simple channel for or tablet) and that can often interact with internet-based voice to one for exchanging text, data, audio, and video services to, for instance, access updates. Most apps are used through the internet. Given technological convergence, by individual users, but the applications that may prove mobile handsets can now function as a wallet, camera, tele- most useful for development are those usually developed vision, alarm clock, calculator, address book, calendar, news- within an ecosystem that involves many different players, paper, gyroscope, and navigational device combined. The including software developers, content providers, network latest smartphones are not just invading the computer space, operators, device manufacturers, governments, and users. they are reinventing it by offering so much more in both Although the private sector is driving the market, social voice and nonvoice services. intermediaries, such as nongovernmental organizations Developing countries are increasingly well placed to (NGOs) play an important role in customizing applications exploit the benefits of mobile communications, with levels to meet the needs of local communities. In many countries, of access rising around the world. Chapter 1 explores the a ready-made community of developers has already devel- implications of the emergence of high-speed broadband oped services based around short message service (SMS) or networks in developing countries, and how the bond instant messaging (IM) and is now developing applications between mobile operators and users is loosening, as for more sophisticated devices. Policy-makers need to create computer and internet companies invade the mobile space, an environment in which players can collaborate as well as with a growing number of handset models now offering compete. That will require rethinking regulations governing Wi-Fi capability. specific sectors such as financial services, health, or educa- The chapter also examines the size and nature of the tion. Governments also play a fundamental role in establish- mobile economy and the emergence of new players in the ing necessary conditions in which mobile communications mobile ecosystem. The emergence of apps, or special soft- can thrive through the allocation of wireless spectrum, ware on handheld devices that interacts with internet-based enactment of vital legislation, and leadership in mobile data services, means that the major issue for the develop- government, or mGovernment. ment community today is no longer basic access to mobile The mobile revolution is right at the start of its phones but about what can be done with phones. More than growth curve. Devices are becoming more powerful and 30 billion apps had been downloaded worldwide by early cheaper. But the app economy requires economies of scale 2012, and they make for an innovative and diverse mobile to become viable. The report argues that now is the time landscape with a potentially large impact on the lives of to evaluate what works and to move toward the commer- people in developed and developing countries alike. Grow- cialization, replication, and scaling up of those mobile ing opportunities for small-scale software developers and apps that drive development. Until recently, most services local information aggregators are allowing them to develop, using mobiles for development were based on text invent, and adapt apps to suit their individual needs. Users messaging. Now, the development of inexpensive smart- themselves are becoming content providers on a global scale. phones and the spread of mobile broadband networks are Indeed, the latest generations of mobile telephony are transforming the range of possible applications. Several sowing social and political as well as economic transforma- challenges lie ahead, notably, the fragmentation that tion. Farmers in Africa are accessing pricing information arises from multiple operating systems and platforms. It through text messages, mothers can receive medical reports is already clear, however, that the key to unleashing the on the progression of their pregnancy by phone, migrant power of the internet for the developing world lies in the workers can send remittances without banks. Elections are palm of our hands. 4 Information and Communications for Development 2012 monitored and unpopular regimes toppled with the help of may limit the economies of scale realizable from expand- mobile phones. Texting and tweeting have become part of ing from pilot programs into mass markets, potentially modern vocabulary. hindering the spread of new and promising applications Mobiles are now creating unprecedented opportunities and services. for employment, education, and entertainment in develop- The full scope and scale of smartphones and tablets for ing countries. This chapter looks beyond specific examples providing services to agricultural stakeholders have yet to to identify the broader trends shaping and redefining our emerge. An enabling environment that can promote the understanding of the word “mobile.� development and use of applications in developing coun- tries must be prioritized to meet the information needs of the agricultural sector. A mobile green revolution Given the dominance of primary commodities in the Keep using the tablets—how mobile economies of many developing countries, chapter 2 explores devices are changing health care the all-important area of mobile applications designed to improve incomes, productivity, and yields within the agri- Chapter 3 examines some of the key principles and charac- cultural sector, which accounts for about 40 percent of the teristics of mobile for health (mHealth), and how mobiles workforce and an even greater proportion of exports in are helping transform and enhance the delivery of primary many developing countries. and secondary health care services in developing countries. To date, voice calls and SMS text messages have proven Mobile health can save money and deliver more effective invaluable in increasing efficiency in smallholder agriculture. health care with relatively limited resources; increasingly, it is They can, for example, provide real-time price information associated with a focus on prevention of diseases and and improve the flow of information along the entire value promotion of healthy lifestyles. chain, from producers to processors to wholesalers to retail- This chapter reviews on-the-ground implementations ers to consumers. The basic functions of the mobile phone of medical health care apps to draw key conclusions about will continue to remain important for reaching the widest how mHealth can best be implemented to serve the needs number of people, but the focus of applications development of people in the developing world, as well as identifying is shifting as the underlying technologies evolve. barriers that must be overcome. It considers some of the Today, increasingly specialized mobile services are fulfill- unique features of the health care sector and the implica- ing specific agricultural functions, while multimedia tions for medical apps in areas such as patient privacy and imagery is being used to overcome illiteracy and provide confidentiality, public and private provision of care, and complex information regarding weather and climate, pest real-time reporting requirements in crisis or emergency control, cultivation practices, and agricultural extension situations. services to potentially less tech-savvy farmers. This chapter Modern health care systems are at a tipping point, as also examines the emerging uses of remote and satellite tech- consumers take on greater responsibility for managing their nologies that are assisting in food traceability, sensory detec- own health care choices, and mobile phones could enable a tion, real-time reporting, and status updates from the field. shift in the locus of decision-making away from the state and It further reviews examples of mobile services in agriculture health institutions to individual patients. to draw key learning points and provide direction on how to The most substantial challenge for mHealth, however, is capitalize on successful examples. the establishment of sustainable business models that can be Mobile applications for agriculture and rural develop- replicated and scaled up. One step toward addressing this ment have generally not followed any generic blueprint. They challenge might be a clearer delineation of roles within the are usually designed locally and for specific target markets, health ecosystem between public and private health care with localized content specific to the languages, crop types, providers. Another significant challenge is the effective and farming methods. Local design offers exciting opportu- monitoring and evaluation of mobiles in health, as pilot nities for local content and applications development but programs continue to proliferate. Executive Summary 5 Mobile money side. Employment opportunities in the mobile industry can be categorized as direct jobs, indirect jobs, and jobs on the This chapter examines the all-important topic of mobile demand side. The contribution of the mobile communica- money as a general platform and critical infrastructure under- tion sector to employment and entrepreneurship to date is pinning other economic sectors. Mobile money has trans- difficult to assess, however, because the seemingly simple formed the Kenyan economy, where mobile-facilitated mobile phone can generate—and occasionally eliminate— payments now equate to a fifth of the country’s gross domestic employment opportunities by creating efficiencies and product (GDP). The impact of mobile money is widening else- lowering transaction and information costs. where too, as it is adopted across commerce, health insurance, The recent rapid innovation in the mobile sector has agricultural banking, and other sectors. Today, the potential of generated significant disruptive technological change and mobile payment systems to “bank the unbanked� and empower uncertainty. This turmoil is also lowering barriers to entry, the poor through improved access to finance and lower trans- however, and generating fresh opportunities for small and action costs is generating growing excitement. Where they young firms and entrepreneurs to displace legacy systems, exist, mature mobile money systems have often spun off inno- innovate, and grow. vative products and services in insurance, credit, and savings. Chapter 5 showcases some of the mechanisms by which When connected on a large scale, evidence suggests that the mobile sector supports entrepreneurship and job the poor are able to use mobile money to improve their creation. Some share similarities with traditional donor livelihoods. Observers remain divided, however, about initiatives, but many are novel ideas, for which the “proof of whether mobile money systems are fulfilling their true concept� has been demonstrated only recently or has yet to be growth potential. Innovative offerings, old and new, can demonstrated. This chapter considers the use of specialized succeed only if there is sufficient demand from consumers business incubators or mobile labs (mLabs) for supporting and firms—a variable missing in many contexts. entrepreneurial activity in the mobile industry, as well as new The mobile money industry exists at the intersection of opportunities that are offered in areas such as the virtual banking and telecommunications, embracing a diverse set of economy (trading goods and services that exist only online) stakeholders, including mobile operators, financial services or mobile microwork (work carried out remotely on a companies, and new entrants (such as payment card firms). mobile device, on micro-tasks, such as tagging images). In some countries, mobile money systems may be subject to It also provides suggestions on how to support entrepre- different regulatory practices and interoperability issues, not neurship and job creation in the mobile industry. In an to mention clashes in culture between banks and mobile industry evolving as quickly as the mobile sector is today, it operators, so developing the necessary cross-sectoral partner- is vital to tailor support to local circumstances and to evalu- ships can prove difficult. In other countries, well-developed ate impact regularly. alternative legacy systems are strong competitors to the development of mobile money systems. This chapter evaluates the benefits and potential impact Using phones to bring governments of mobile money, especially for promoting financial inclu- and citizens closer sion in the developing world. It provides an overview of the In the public sphere, mobiles now serve as vehicles for key factors driving the growth of mobile money services, improved service delivery and greater transparency and while considering some of the barriers and obstacles hinder- accountability. Today, governments are beginning to embrace ing their deployment. Finally, it identifies emerging issues the potential for mobile phones to put public services literally that the industry will face over the coming years. into the pocket of each citizen, create interactive services, and promote accountable and transparent governance. Chapter 6 identifies a range of uses for mobiles in Get a phone, get a job, start a government (mGovernment) that supplement existing business public services, expand their user base, and generate spin- The global mobile industry is today a major source of off services. The revolutionary aspect to mGovernment lies employment opportunities, on both the supply and demand in making government available, anytime and anywhere, to 6 Information and Communications for Development 2012 anyone. The chapter also provides a range of examples of • Limiting spectrum hoarding, which could distort mGovernment from around the world as well as a range of competitive conditions in the market best practices and recommendations. It demonstrates how • Fostering the development of national backbone broad- countries can play a constructive role in enhancing sustain- band networks ability and enabling scale, while maximizing the impact of mGovernment programs. • Encouraging infrastructure and spectrum sharing An important conclusion is that bottom-up ad hoc Demand-side policies aim at boosting growth in the approaches to mGovernment may endanger economies of adoption of wireless broadband services by addressing barri- scale. Top-down coordinated approaches may be preferable, ers to adoption and fostering the development of innovative since they can cut costs in designing, deploying, and operat- broadband services and applications pulling users’ demand ing apps; consolidate demand for communication services toward mobile broadband. The chapter reviews the follow- across government, thereby eliminating duplication; and ing demand-side policy recommendations: include focused actions to build capacity and skills. • Improving the availability and affordability of broad- Emerging best practices suggest that any government band-enabled devices considering the opportunities inherent in mGovernment should focus on enabling technological transformation and • Boosting the affordability of broadband services building the institutional capacity needed to respond to citi- • Fostering the development of broadband services and zens’ demands. Governments looking to adopt mobile tools applications to become responsive, accountable, and transparent should The chapter concludes that appropriate policy action bear in mind that this process will prove successful and truly requires addressing both the supply- and demand-sides of the transform the government-citizen relationship only when mobile broadband ecosystem. Policy-makers must evaluate governments take into account both elements—“mobile� local market conditions before applying specific policies and “government.� addressing bottlenecks or market failures. The most common breakdowns on the supply side are lack of available spectrum Onward and upward to mobile and inadequate backbone networks; on the demand side, the broadband main constraints are lack of affordable mobile devices and broadband services, as well as limited local applications and Chapter 7 distinguishes between supply-side policies (which content. Ultimately, policy-makers must determine which seek to promote the expansion of wireless broadband policies to adopt, and how to implement them, based on networks) and demand-side policies (which seek to boost domestic circumstances and the likely effectiveness of the adoption of wireless broadband services) in the mobile policy for broadband diffusion in the context of each country. broadband ecosystem. Supply-side policies seek to address bottlenecks and market Appendixes failures that constrain network expansion and provide incen- tives for broader wireless broadband coverage. The chapter The Country Tables in the appendix to this report provide reviews the following supply-side policy recommendations: comparative data for some 152 economies with populations of more than 1 million and summary data for others, with • Boosting the availability of quality spectrum to deploy at-a-glance tables focusing on the mobile sector. The report cost-effective wireless broadband networks is complemented by the World Bank’s annual Little Data • Eliminating technological or service restrictions on spec- Book on Information and Communication Technology, which trum presents a wider range of ICT data. The Statistical Appendix reviews the main trends shaping • Focusing on expanding network coverage rather than on the sector and introduces a new analytical tool for tracking profiting from spectrum auctions the progress of economies at different levels of economic • Requiring transparency in traffic management and safe- development in widening access, improving supply, and guarding competition stimulating demand for mobile services. Executive Summary 7 Chapter 1 Overview Michael Minges obile communication has arguably had a Developing countries are increasingly well situated to M bigger impact on humankind in a shorter period of time than any other invention in human history. As noted by Jeffrey Sachs (2008), who exploit the benefits of mobile communications. First and foremost, levels of access are high and rising. The number of mobile subscriptions in low- and middle-income countries directed the United Nations Millennium Project: “Mobile increased by more than 1,500 percent between 2000 and phones and wireless internet end isolation, and will there- 2010, from 4 to 72 per 100 inhabitants (figure 1.1a). Second, fore prove to be the most transformative technology of the age profile of developing nations is younger than in economic development of our time.� developed countries, an important advantage in the mobile The mobile phone has evolved from a simple voice device world where new trends are first taken up by youth.1 Those to a multimedia communications tool capable of download- under age 15 make up 29 percent of the population in low- ing and uploading text, data, audio, and video—from text and middle-income economies but just 17 percent in high- messages to social network updates to breaking news, the income nations (figure 1.1b). Third, developing countries latest hit song, or the latest viral video. A mobile handset can are growing richer, so more consumers can afford to use be used as a wallet, a compass, or a television, as well as an mobile handsets for more than just essential voice calls. alarm clock, calculator, address book, newspaper, and camera. Between 2000 and 2010 incomes in low- and middle-income Mobiles are also contributing to social, economic, and nations tripled (figure 1.1c). Fourth, the mobile sector has political transformation. Farmers in Africa obtain pricing become a significant economic force in developing information via text messages, saving time and travel and economies. Mobile revenues as a proportion of gross making them better informed about where to sell their prod- national income (GNI) rose from 0.9 percent in 2000 to ucts, thereby raising their incomes (World Bank 2011a, 353). 1.5 percent in 2010 (figure 1.1d). In India barbers who do not have a bank account can use These changes are creating unprecedented opportunities mobiles to send money to relatives in villages, saving costs for employment, education, and empowerment in develop- and increasing security (Adler and Uppal 2008, 25). Elec- ing countries. Local content portals are springing up to tions are monitored and unpopular regimes toppled with satisfy the hunger for news and other information that the help of mobile phones (Brisson and Krontiris 2012, 75). previously had been difficult to access. The nature of the Texting and tweeting have become part of the vocabulary mobile industry itself is changing dramatically, opening new (Glotz, Bertschi, and Locke 2005, 199). opportunities for developing nations in designing mobile 11 Figure 1.1 The developing world: young and mobile a. Mobile subscriptions (per 100 c. GNI per capita (current US$), low- people), low- & middle-income economies & middle-income economies $3,317 72 $1,132 4 00 10 00 10 20 20 20 20 b. Population ages 0–14 (% of total), 2010 d. Mobile revenue (% of GDP) low- & middle- income economies 1.5% Low- & middle-income 29 0.9% High-income 17 World 27 00 10 20 20 Sources: Adapted from World Bank 2011b and author’s own estimates. applications and developing content, piloting products and consumers to add content and applications to their mobile services, and becoming innovation hubs. Trendy mobile phones. Mobile operators are struggling to keep pace with an products and services may be launched in Silicon Valley or explosion of data, while networks are converging toward Helsinki, but mobile manufacturing usually takes place else- Internet Protocol (IP) technologies and relying on content where, creating huge opportunities to service, support, and and data to substitute for declining voice revenues. An develop applications locally. While key mobile trends are increasingly hybrid wireless communications ecosystem will generally adopted around the world, regions such as East evolve over the coming years. Asia are forging their own path for content and applications. Although mobile communication is rapidly advancing in New mobile innovation centers are springing up in Beijing, most parts of the world, a significant segment of the world’s Seoul, and Tokyo, with expertise in specific markets such as population remains unable to use the latest mobile tech- mobile gaming and contactless banking. nologies. Mobile broadband coverage is often limited to The emergence of mobile broadband networks, coupled urban areas, and current smartphone prices are not afford- with computer-like handsets, is causing rapid shifts in the able for many. Nonetheless, developing-country users are ecosystem of the sector. The bond between mobile operators using what they have. Text messaging, mobile money, and and users is loosening as computer and internet companies simple internet access work on many low-end phones. An invade the mobile space and handsets increasingly offer Wi-Fi emerging ecosystem of local developers is supporting capability. Online stores have created a new way for narrowband mobile communicating through scaled-down 12 Information and Communications for Development 2012 web browsers, text messaging, social networking, and pay- the average Moroccan (figure 1.2a). Price is a major factor in as-you-go mobile data access. For many users, especially in calling patterns, with a clear relation between monthly rural areas, these changes are happening where finding the minutes of use and the price per minute. Interconnection electricity to recharge a phone is more difficult than fees between operators are a main determinant of price. In purchasing prepaid airtime. some countries these wholesale rates do not reflect underly- These developments have major implications for the state ing costs that drive up the price of mobile calls. A second of access to information and communication technologies factor relates to whether the subscriptions are paid in (ICTs) in the 21st century. Rich countries have the luxury of advance (prepaid) or paid on the basis of a contract (post- both wired and wireless technology, of both personal paid). Prepaid subscriptions are much more popular in computers (PCs) and smartphones. Developing countries developing economies, where incomes may be less stable, tend to rely mainly on mobile networks, and phones already but postpaid contracts tend to generate higher usage per vastly outnumber PCs. Applications have to be different to subscriber (figure 1.2b). work on small screens and virtual keyboards, while conver- As with fixed networks, a growing proportion of traffic gence is happening apace. The developed world is also now from mobile devices is moving to Voice over Internet Proto- becoming “more mobile,� with average screen size shrinking; col (VoIP), often routed over Wi-Fi rather than the cellular while the developing world is now becoming, “more network, thereby avoiding per-minute usage charges. connected,� forging ahead with the shift from narrowband According to CISCO, a major supplier of IP networking to broadband networks on a mobile rather than a fixed plat- equipment, mobile VoIP traffic is forecast to grow form. Demography is on the side of the developing world, 42 percent between 2010 and 2015.2 Although mobile VoIP and the economies of scale gained from serving these accounts for a tiny share of total mobile data traffic, its expanding markets may push the ICT industry as a whole in value impact on mobile operators is much greater. Skype, a the direction of a post-PC, untethered world. leading VoIP provider, has reported over 19 million down- One of the challenges facing a report of this nature is loads of its iPhone application since its launch in 2009. In that the industry is evolving so rapidly. What is written addition to voice and video, Skype processed 84 million today is often outdated tomorrow. In addition, given the SMS text messages during the first half of 2010.3 One study novelty of many developments and a lack of stable defini- forecasts 288 million mobile VoIP users by 2013 (van tions and concepts, official data are scarce or fail to address Buskirk 2010). important market trends. Information from secondary sources is often contradictory, inconsistent, or self-serving. Not just for voice anymore Information about mobile culture is particularly scarce in Although voice is still the main revenue generator, its growth developing countries. Nevertheless, certain trends are visi- has slowed (TeleGeography 2012) as data and text-based ble, and this opening chapter explores key trends shaping applications have grown in popularity, their use made possi- and redefining our understanding of the word “mobile� as ble by advances in cell phone technology (box 1.1). Mobile an entrée to the review of different sectors in the chapters applications are the main theme of this book. For many that follow. people, a mobile phone is one of the most used and useful appliances they own. Built-in features are indispensable to many for checking the time, setting an alarm, taking photos, How mobile phones are used performing calculations, and a variety of other daily tasks. Voice Downloadable applications can extend functionalities. With all the attention given to mobile broadband, smart- A number of nonvoice applications use wireless networks phones, and mobile applications, it is sometimes easy to forget on a one-off basis (to download, for example); other appli- that voice communication is still the most significant function cations (such as incoming email notifications) are always on. and the primary source of revenue for mobile operators. Stand-alone features mean that users do not necessarily need Voice usage varies considerably both across and within to use a mobile network. For example, downloading of countries. For example, the average Chinese user talks on a content or applications can be carried out from a PC and mobile phone more than seven times longer per month than then transferred to a mobile phone, or such tasks can be Overview 13 Figure 1.2 Talking and paying: mobile voice use and price for selected countries, 2010 a. Monthly minutes of use and price per minute b. Minutes of use by contract type 600 567 600 $0.25 521 500 500 494 433 449 $0.20 $0.20 400 376 400 $0.16 $0.15 $0.15 331 300 300 280 279 $0.10 206 202 214 191 $0.08 200 200 158 $0.05120 114 96 $0.05 100 95 100 $0.04 71 68 71 48 $0.01 $0.01 $0.01 $0.01 $0.02 0 $0.00 0 be a n mb a A ia ng ria h za ile ut tan ca or l co co ca ia nia M azi Uz Chin ta Ca Indi es od ys fri oc oc fri Ka Ch Ba lge ma kis So hs Br lad ala hA hA or k Ro M M ut So Monthy minutes of use Price per minute (US$) Blended Contract Prepaid Source: Mobile operator reports. Note: Data refer to largest mobile operator (by subscriptions). Price per minute is calculated by dividing minutes of use by average revenue per user. Box 1.1 Mobile phones and applications The use of mobile phones has evolved dramatically over time and will continue to do so at an ever faster pace, so it is important to define some terms that are used throughout this report, while noting that these definitions are not necessarily stable. Many mobile handsets, particularly in the developing world are so-called basic phones, based on the second-generation (2G) GSM (Global System for Mobile communications) standard, first introduced in 1991. GSM offers a number of different services embedded in the standard and therefore available on all GSM- compatible devices, however basic. These include short message service (SMS) text messages of up to 160 characters, and instant messaging using the USSD (Unstructured Supplementary Service Data) protocol. Many of the older “mobile applications,� particularly in the developing world, are based on SMS or USSD, because they do not require additional data services or user downloads and are available on virtually any device. Strictly speaking, however, these should be considered network services rather than applications (box table 1.1.1). Internet-enabled hand- sets, or feature phones, were introduced with the launching of data services over mobile networks in the early 2000s. These phones supported transmission of picture messages and the downloading of music and often included a built-in camera. Smartphones appeared in the late 2000s. They typically feature graphical interfaces and touchscreen capability, built-in Wi-Fi, and GPS (global positioning system) capability. Smartphones with memories and internet access are also able to download applications, or “apps,� pieces of software that sit on the phone’s memory and carry out specific functions, (continued next page) 14 Information and Communications for Development 2012 Box 1.1 (continued) Box Table 1.1.1 Mobile devices and their capabilities Device Capabilities Device Capabilities Basic mobile Network services, including: Smartphone As Featurephone plus: phone Voice telephony and voice mail Video camera SMS (short message service) Web browser USSD (unstructured supple- GPS (global positioning system) mentary service data) 3G+ internet access SMS-based services, such as Mobile operating “platform� (such mobile money as iOS, Android, Blackberry) Ability to download and manage USSD services, such as instant applications messaging VoIP (Voice over Internet Protocol) Mobile TV (if available) Removable memory card Featurephone As basic mobile phone plus: Tablet As smartphone plus: Multimedia Messaging Service Front and rear-facing video (MMS) cameras (for video calls) Still picture camera Larger screen and memory capability MP3 music player Faster processor, enabling video 2.5G data access playback Touchscreen with virtual keyboard USB (universal serial bus) port Note: The list of capabilities is not exhaustive, and not all devices have all features. like accessing websites or reporting the phone’s location and status. In this report, the term “apps� is used to denote such applications that may be downloaded and used on the device, either with or without a fee, in a stand-alone mode. The most popular apps are games. More than 30 billion apps had been downloaded as of early 2012 (Gartner 2012; Paul 2012). Using mobile applications for development usually requires more than simply downloading an app to a user device, however. Specifically, the most useful mobile appli- cations, such as those discussed in this report, typically require an ecosystem of content providers (for instance, reporting price data for agricultural produce, discussed in chapter 2) or agents (such as those providing cash upload facilities for mobile financial services, discussed in chapter 4). These kinds of “ecosystem-based mobile applications� are the main topic of this report. However, technological change continues apace. Newer generations of mobile application may be “cloud based,� in the sense that data is stored by servers on the internet rather than locally on the device. Applications that use HTML5 (the current generation of hypertext mark- up language), for instance, may not require any software to be downloaded. Such applica- tions may have the advantage that they can be used independently of the network or mobile device that the user is currently using. For instance, a music track stored on the “cloud� might be accessed from a user’s tablet, smartphone, or PC, and even when the user is roam- ing abroad. But such a shift depends on much lower prices, without monthly caps, for mobile data transmission. Overview 15 carried out over Wi-Fi. Indeed, the “mobile� in “mobile (figure 1.4a) accounting for 80 percent of operator applications� refers as much to the type of device as the revenue from value-added-services, or $106 billion manner of usage. (Informa 2011). This is an attractive revenue source for A survey (Pew Research Center 2011) carried out across a operators because the cost of transmitting text messages is range of countries at varying economic levels and in differ- so low. Although its use in some countries is now starting ent regions illustrates the varied uses of mobile phones to decline in favor of instant messaging and phone-based (figure 1.3). After voice usage, text messaging is the most email, SMS remains an alternative for costly voice calls in widely used: in more than half the countries surveyed, three- some countries or suffices for users who do not have quarters of mobile phone owners sent text messages; in access to the internet on their mobiles (or do not know Indonesia virtually all mobile users sent text. Although usage how to use it). Messaging has become popular as a feed- rates vary, mobile devices were used to access the internet in back mechanism for voting on TV reality shows and a way all surveyed countries, with almost a quarter of cell phone of providing value-added services such as banking or pric- owners using this feature on average. ing information. As a form of asynchronous (that is, non- real-time) communication, it is particularly useful for Messaging coordinating meetings or reaching correspondents who Despite the attention focused on more glamorous mobile are not available to talk (Ling and Donner 2009). Text applications, text messaging (or SMS) is a popular and messaging is also important for applications in the profitable nonvoice application in many countries. Close mobile-for-development arena. Many agricultural pricing to 5 trillion text messages were sent worldwide in 2010 and health programs for rural dwellers revolve around Figure 1.3 Mobile phone usage around the world, 2011 On your cell phone, do you regularly… Send text messages Take pictures or video Use the Internet China 80 54 37 Egypt, 72 58 15 Arab Rep. India 49 26 10 Indonesia 96 38 22 Jordan 63 43 23 Kenya 89 31 29 Lebanon 87 33 19 Mexico 82 61 18 Pakistan 44 9 6 Turkey 64 44 22 Ukraine 72 48 19 Median 75 50 23 0 25 50 75 100 0 25 50 75 100 0 25 50 75 100 percentage percentage percentage Source: Pew Research Center 2011. Note: Survey carried out in March–May 2011. 16 Information and Communications for Development 2012 Figure 1.4 Worldwide SMS and Twitter traffic 5.0 a. SMS traffic 12 14 b. Tweets per day (millions) 12 4.0 10 4.6 10 7 Twitter 3.0 8 launched 3.5 5 March 2006 340 2.0 2.7 6 4 2 4 1.9 1.0 140 1.4 2 0.8 50 0 0.005 0.3 2.5 35 0 0 07 08 09 9 6 0 1 2 05 06 07 08 09 10 c-0 -0 -1 -1 -1 n- n- n- 20 20 20 20 20 20 ar ar ar ar Ja Ja Ja De M M M M Per year (trillions) Per day (millions) Millions Sources: World Bank estimates (panel a); Twitter 2010, 2011 (panel b). SMS, and text messaging is used by several governments such as Opera, are suited to featurephones.9 On most for citizen alerts. smartphones, users are encouraged to download applica- Twitter, a social networking “microblog� launched in tions from special app stores, sometimes belonging to the 2006, is also based on short messages, or “tweets,� which operator but increasingly owned by the device platform are intentionally similar to the length of a text message (such as Apple, Android, Windows, and Blackberry). That and therefore a good fit for mobile phone use.4 Around arrangement has the convenience of ensuring that the 40 million people (some 37 percent of all Twitter users) application is suitable for the smaller screen size of mobile were “tweeting� from their mobile devices in April 2010; a devices, although the full range of internet content is still year later that number exceeded 100 million (Watters available through a web browser. 2010). 5 By March 2012 Twitter users were sending Social networking is popular, ranking in the top 10 340 million tweets a day (figure 1.4b).6 Twitter is inte- among mobile internet use in practically every country. grated with SMS, so tweets can be sent and received as Facebook is predominant except in countries such as China text messages. Twitter short codes have been implemented and the Russian Federation, where local social networking for several countries so that most SMS tweets are charged sites are used. More than 425 million people accessed Face- at domestic rates. Twitter is working with mobile opera- book through their mobile devices in December 2011.10 tors to lower the cost of sending tweets through SMS or East Asia in particular is bucking the trend toward use of USSD or even to make them free. Twitter has rapidly global applications. The main reason is large domestic emerged as a tool for social activism and citizen engage- markets (such as China, Japan, Republic of Korea), which ment ranging from the Delhi police tweeting traffic use non-western alphabets and create huge demand for local updates7 to tweeting the revolution in the Arab Republic content and applications. China Mobile, the world’s largest of Egypt.8 mobile operator, has developed its own applications that mimic global trends in areas such as mobile money, ebooks, Web browsing video, music, and gaming. But these application are basically Access to the internet via a web browser on a mobile device closed systems, unfathomable to users that do not speak varies across countries depending on costs, education, Chinese and not easily exportable to other countries. speeds, and content. Overall, usage is growing, however, The most downloaded applications for smartphone with an estimated 10 percent of global internet access portals include utilities for tools such as mapping, social coming from mobile phones in 2010, up from 4 percent in networking, chatting, and messaging (table 1.1). 2005. Most popular websites have special versions adapted One genre in every list of top downloads across all appli- to mobile devices, although customized mobile browsers, cation portals and all regions is games. The popularity of Overview 17 Table 1.1 Top mobile applications, June 2011 Android Apple Blackberry Paid Free Paid Free Paid Free 1 Beautiful Widgets Google Maps Sonic/Sega All-Star Turtle Fly One Touch Flashlight BlackBerry Messenger ($2.85) Racing ($4.99) ($0.99) 2 ROM Manager Facebook Angry Birds ($0.99) Line Jumper Super Color LED UberSocial ($5.86) ($1.99) 3 Fruit Ninja ($1.25) Pandora Fruit Ninja ($0.99) Tiny Tower MegaHorn ($0.99) Copter 4 Robo Defense Angry Birds Tiny Wings ($0.99) Cars 2 Lite Tetris ($0.99) Facebook 5 Root Explorer ($3.83) YouTube Angry Birds Rio Hanging with Photo Editor Ultimate WhatsApp Messenger ($0.99) Friends ($1.99) 6 PowerAMP ($5.17) Words With Cars 2 ($0.99) Racing Penguin Angry Farm ($0.99) foursquare Friends 7 WeatherBug ($1.99) Advanced Task Cut the Rope ($0.99) Sea Battles Lite Chat for Facebook Twitter Killer ($0.99) 8 Better Keyboard Angry Birds Rio Hanging with Friends Dream Bride BeAlert ($0.99) Pixelated ($2.99) ($1.99) 9 DocumentsToGo music download Camera+ ($1.99) Super World A+ Chat ($0.99) Free Chat for Facebook ($14.99) Adventure 10 Titanium Backup Yahoo! Mail Angry Birds Seasons Facebook Next Dual Pack Windows Live ($6.05) ($0.99) ($0.99) Messenger Source: Respective application stores, June 30, 2011. games has made millionaires of some application developers more comfortable using similar thought processes in (box 1.2) and attests to the significant financial impact the areas that are not entertainment-oriented, including gaming sector is having on the mobile industry. health or business. Games are particularly big in East Asia, accounting for almost half of the estimated global mobile gaming revenue Data traffic of $5.5 billion in 2008 (Portio Research 2009). In Korea the mobile games sector was worth 424.2 billion won Growing mobile data usage is triggering explosive growth in ($390 million) in 2010 even though games downloaded traffic. Social networking entails considerable photo and from smartphone application stores operated by Apple and video exchange and is the leading generator of traffic in Android were considered illegal because of the government many countries (Opera Software 2011). YouTube, the video ratings system.11 That ratings system is set to be loosened, portal, ranks among the top 10 web applications in most which will likely lead to further market growth. In Japan the countries. According to CISCO (2012), video is expected to mobile games market was estimated to be worth 88.4 billion account for more than two-thirds of all mobile traffic in yen ($1 billion) in 2009 (Toto 2011). China Mobile reported 2016, and mobile data traffic will increase 18-fold between that it had 4.6 million paying users of its online library of 2011 and 2016. 3,000 games in 2010.12 Mobile operators are struggling to handle all this data The popularity of mobile games and the size of the and control the traffic. They are adding as much capacity as sector holds opportunities in the areas of software devel- they can to their networks within investment and spectrum opment, virtual cash, and local customization (Lehdon- constraints. They are also off-loading traffic to Wi-Fi wher- virta 2011). The traits of game playing, such as acquiring ever possible. The most common method for controlling, or points, leveling, and solving challenges are also entering “shaping,� traffic is through data caps on mobile data plans. other fields where applications are used, such as educa- Few operators offer truly unlimited mobile data plans, and tion or social media, in a process called “gamification.� the cost of exceeding caps can be steep, with users facing a The thinking is that users who have become accustomed loss or severe disruption of service and dramatically reduced to using games on their mobile devices would then be speeds. The case of Hong Kong SAR, China, illustrates well 18 Information and Communications for Development 2012 Box 1.2 How to make a million from Angry Birds Angry Birds has been a worldwide game sensation. It was the number one Apple iPhone download in countries ranging from Pakistan to Peru and the Philippines to Portugal. Rovio Mobile, a Finnish firm founded in 2003, developed Angry Birds.a In 2009 Rovio released Angry Birds for the iPhone. The company’s development of Angry Birds outlines the relationships between game developers, publishers, and giant gaming companies. Rovio initially worked with publisher Chillingo to develop the iPhone version of Angry Birds, keeping the rights for versions on other platforms. Following the sale of Chillingo to gaming company Electronic Arts in October 2010, Rovio developed its own Angry Birds versions for other mobile systems such as Android and Nokia. It is also leveraging its Angry Birds success by expanding into merchandizing with T-shirts and other products. According to one source, Angry Birds had over 5 million downloads from the Apple app store during the first six months of 2010 alone (Parker 2010). At $0.99 a download, the game generated at least $5 million in revenue during that period. a. http://www.rovio.com. the impending wave of data usage that will soon be hitting mobile payments widened this ecosystem, but operators other countries (figure 1.5a). During 2011 average monthly essentially remained the gatekeepers. mobile data usage increased by more than 70 percent to over 500 megabytes (MB) per 2.5G or 3G user. Although Hong The app revolution Kong is an advanced economy, and therefore well ahead of Operator control started to break down with the emer- most developing nations, the same trends can be expected gence of smartphones and other devices that run specific elsewhere at a later date. CISCO (2012) forecasts monthly mobile operating systems, incorporate built-in Wi-Fi, and usage to reach more than 10 exabytes (that is, 1 billion giga- allow users to purchase content and applications through bytes) in 2016, with smartphones, laptops, tablets, and special online stores. The first kink in the direct relation- mobile broadband networks leading the charge (figure 1.5b). ship between operators and users was the BlackBerry, This subject is developed further in chapter 7. introduced by Canadian company Research in Motion (RIM) in January 1999. Marketed as “wearable wireless email,�13 the BlackBerry could arguably be called the world’s The changing mobile ecosystem first smartphone. Revolutionary at the time, it allowed Before the emergence of smartphones, network operators subscribers to receive email using RIM’s proprietary Enter- had historically controlled the mobile ecosystem. They prise Server. The BlackBerry was a big hit within the corpo- were the main point of interface for users regarding devices rate world because it ensured that key personnel could and applications. Although users were free to purchase receive emails anytime, anywhere. RIM later expanded their own handsets, operators typically subsidized them BlackBerry distribution to reach mass markets, earning $20 where regulation allowed them to do so, at least for the billion in revenue in its 2010 fiscal year. RIM has moved postpaid segment. Users who wanted to talk, send a into emerging markets and into social networking through message, or access the internet did so over the mobile oper- its BlackBerry Messenger. The company shipped 52 million ator’s network. Access was often through an operator’s devices in its 2010 fiscal year and had some 55 million “walled garden�—a portal where content providers paid subscribers in November 2010 (figure 1.6a).14 BlackBerry operators to feature their applications. If users went App World launched in 2009, but having been an early outside the walled garden, they typically had to pay extra. trendsetter, it is now struggling to keep up with develop- Developments such as value-added text messages and ments elsewhere. Overview 19 Figure 1.5 Data, data everywhere a. Monthly mobile data usage in Hong Kong SAR, China b. Forecast global totals by origin device, 2011–16 Hong Kong SAR, China Exabytes a month 4,500 600 12 Forecast data shares 4,000 500 10 3,500 3,000 400 8 2,500 300 6 2,000 1,500 200 4 1,000 100 2 500 0 0 0 11 12 13 14 15 16 02 03 04 05 06 07 08 09 10 11 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 Mobile data (GB) Per user (MB) Other portable devices (2.2%) M2M (4.7%) Home gateways (4.8%) Non-smartphones (5.7%) Tablets (10.0%) Laptops and netbooks (24.2%) Smartphones (48.3%) Sources: OFTA 2012 (panel a); CISCO 2012 (panel b). Note: The compounded annual growth rate for mobile data usage is projected to be 78 percent between 2011 and 2016. Figure 1.6 Apples and Berries: iPhone sales and Blackberry subscriptions a. iPhone units sold b. BlackBerry subscribers 80 60 72 55 70 50 60 41 40 50 Millions Millions 40 40 30 25 30 21 20 20 14 12 10 8 10 4.9 1 2.5 0 0 07 08 09 10 11 04 05 06 07 08 09 10 20 20 20 20 20 20 20 20 20 20 20 20 Sources: Apple and RIM operating reports. Note: Data for Apple refer to fiscal years ending September 25. Data for Blackberry refer to fiscal years ending March. The industry changed dramatically with the introduction online stores and also by mobile carriers. In addition to the of Apple’s touchscreen iPhone in June 2007, followed by the App Store, iPhone users can download music and video launch of its App Store in July 2008.15 The exclusive agree- from the iTunes store and ebooks from the iBookstore. ments that Apple initially made with mobile operators have By simplifying and taking ownership of the application now largely ended. In January 2010 the company crossed platform, handset vendors were able to exert control over the another milestone, introducing the iPad, its tablet computer. quality of applications on offer and also to create a market for All Apple mobile devices (such as iPhone, iPad, and the iPod purchasing them. Although the majority of downloaded appli- music player) are powered by the iOS mobile operating cations are still free, users are urged to upgrade to paid content system. The iPhone is distributed through Apple’s retail and or subscriptions, if only to get rid of advertising. By February 20 Information and Communications for Development 2012 2011 Apple had downloaded more than 25 billion applications In 2011 it forged an agreement with Microsoft to begin offer- from the App Store. Sales of the iPhone grew from 1.4 million ing the Windows operating system on its smartphones.17 in 2007 to 72 million in 2011 (figure 1.6b). Revenues from the The rise of smartphones thus sparked tremendous shifts iPhone and related products and services grew to $47 billion in in the mobile ecosystem. A user can now bypass mobile 2011, accounting for 44 percent of Apple’s total sales.16 An networks completely by downloading content and programs equipment-selling business is rapidly becoming a software- through application stores using Wi-Fi. One survey reported and-services industry, with operators scrambling to provide that half the respondents used Wi-Fi to download applica- the spectrum bandwidth to carry the heavy volumes of data tions to their mobile phones (In-Stat 2011). Second, users traffic while plotting their own applications portals. can use VoIP or other applications to communicate instead Android, Inc., was founded in 2003 to develop mobile of the operator’s mobile voice service. Third, most handset phone operating systems and then purchased by search giant manufacturers are essentially constrained to using the Google in 2005. Google made the Android software open Android or Windows mobile operating systems for their source to encourage programmers and handset manufactur- handsets because RIM and Apple brand their own devices. ers to develop applications and products. The first Android As a result of the rise of the smartphone, operators have handset, the HTC Dream, was launched in October 2008. much less control over the mobile ecosystem. They risk being Google itself has self-branded several Android phones and “genericized,� where users do not care about the mobile developed Android Market (now called Google Play), a network brand but instead whether it has the fastest speed, portal for obtaining Android applications. By the fourth best coverage, cheapest prices, highest quality, or biggest quarter of 2011 Android had captured just over half the subsidy for popular handsets. Prepaid users, in particular, market for smartphone operating systems (Gartner 2012). have little brand loyalty, with high rates of churn in markets Google Play offers more than 400,000 applications with over where mobile number portability is a regulatory obligation. 10 billion downloaded by January 2012 (Paul 2012). In some ways, this process is a repeat of the one that occurred Another significant player is mobile equipment manufac- in the early 2000s when the rise of the internet threatened to turer Nokia. It has traditionally had a large market share of commoditize the “dumb pipes� of telecom operators, only the handset market, especially in the developing world now it is the mobile operators that are under pressure. At the (figure 1.7). Nokia’s mobile operating system, Symbian, is same time, the emergence of HTML5 could cause another installed on most of these handsets. Thus far, however, Nokia disruption in the industry. With the HTML5 standard, apps has failed to capture a large share of the smartphone market. can be run directly from web browsers, freeing users from Figure 1.7 Changing market share of mobile handset sales by operating system 2008 2011 Microsoft 2% Microsoft 12% Other 3% iOS (Apple) 11% iOS (Apple) 24% Symbian (Nokia) 12% Research In Other 10% Motion 20% Android 0% Research In Motion 9% Android 50% Symbian (Nokia) 47% Sources: Adapted from Gartner 2012. Overview 21 being locked in to a proprietary operating system and creat- This approach ties users to the brand because they cannot ing a new distribution channel for application developers use the content they have purchased if they switch brands. (A.T. Kearney 2011). On the other hand, companies like Amazon, which makes the Kindle ebook reader, sell software applications that Mobile content allow Kindle ebooks to be read on multiple platforms. The evolution of handsets has driven content providers and Similarly, Netflix movie streaming is available across a aggregators to the mobile industry. In the early days, content number of platforms. As cloud computing invades the largely consisted of ringtones and screen pictures down- mobile space, it will be possible to run applications loaded to customize simple mobile phones. As handsets remotely instead of having to purchase and download become more sophisticated and included internet access, them to the device. This development will create more more and more of the “big� internet can be reformatted to subscription-like services rather than single downloads. mobile content, making the “third� screen (after television This is good news for developing nations because it lowers and PCs) a desirable outlet for the content industry. Content the cost of applications and content. But to take advantage providers have also been aided by the rise of application of the cloud, users will need good mobile broadband stores, which allow users to navigate easily to online super- connectivity. markets to satisfy their content cravings. While big technology and media companies dominate Mobile-enabled social and economic content distribution and to some extent content creation, trends there are opportunities for small software developers and local information aggregators. Examples of these aggrega- Research shows that mobile networks are having a growing tors include: impact on the economy. One of the earliest and frequently cited studies on the subject was carried out by three consult- • Seven out of ten Brazilian internet users visit Brazil’s ants from the Law and Economics Consulting Group. Using UOL internet portal, formerly Universo Online. It created data from 92 countries between 1980 and 2003, they found a mobile version, UOL Celular, with more than 1,000 that an increase of 10 mobile subscriptions per 100 people daily news, weather, and traffic reports. It ranks as the raised GDP growth by 0.6 percent (Waverman, Meschi, and 10th most visited site by Brazilian Opera mobile browser Fuss 2005). A similar study using data through 2006 found users and the second-leading local site. that a 10 percent increase in mobile penetration in develop- • Detikcom is the third most visited site by Indonesian ing countries was correlated to a 0.8 percent increase in Opera users. It was launched in 1998 and introduced a economic growth (Qiang and Rossotto 2009). Several stud- mobile version in 2002, significantly contributing to ies also find that growth in mobile networks is positively growth. It envisions itself as a new media company with correlated to foreign direct investment (Lane et al. 2006; partnerships for content and relationships with the coun- Williams 2005). try’s mobile operators to ensure distribution across the Mounting evidence also shows the microeconomic country’s mobile networks. impact of mobile in specific countries and industries. The benefits typically accrue from better access to information • In South Africa, News24 is a leading portal with updated brought about through mobile and are typically related to breaking news. It has a dedicated WAP (wireless access lower transactions costs, savings in travel costs and time protocol) version for mobile phones. It had more than spent traveling, better market information, and opportu- 500,000 unique visitors to its mobile site in December nities to improve one’s livelihood (Jensen 2007; Salahud- 2010, up 200 percent over the previous year.18 din et al. 2003; Aker 2008; see also tables 1.2 and 2.1 and The emergence of cloud computing and multiple types box 1.3). of devices (PCs, tablets, mobile handsets) is creating differ- ent distribution markets. On the one hand, companies like Mobile for development Apple produce content only for their own brand. Apple’s As noted by the United Nations Development Programme iBooks, for example, can be read only on Apple devices. “Mobile phones can enhance pro-poor development . . . 22 Information and Communications for Development 2012 Table 1.2 Mobile and the Millennium Development Goals MDG Example Poverty and hunger A study on grain traders in Niger found that cell phones improved consumer welfare (Aker 2008). Access to cell phones allowed traders to obtain better information about grain prices across the country without incur- ring the high cost of having to travel to different markets. On average grain traders with cell phones had 29 percent higher profits than those without cell phones. In the Niger example, demand sprang up organically rather than through a specific program. Universal education According to a survey of teachers in villages in four African countries, one-quarter reported that the use of mobile phones helped increase student attendance. A main factor was that teachers could contact parents to enquire about their child’s whereabouts (Puri et al, n.d.). Mobile phones have also been used in Uganda to track school attendance so that school administrators can see patterns in attendance, for instance by village, by day of the week, and by season. Tracking attendance for pupils indirectly also tracks absenteeism among teachers (Twaweza 2010) Gender equality A study looking at gender differences in the availability and use of mobile phones in developing countries reported that 93 percent of the women who had mobiles felt safer because of the phone, 85 percent felt more independent, and 41 percent had increased income or professional opportunities (GSM Association 2011). The report found that closing the mobile gender gap would increase revenues for mobile operators by $13 billion. Child health A program using text messaging to identify malnutrition among rural children in Malawi is notable for its impact on the speed and quality of the data flows.a Using a system called RapidSMS, health workers in rural areas were able to transmit weight and height information in two minutes instead of the two months needed under the previous system. The data entry error rate was significantly improved to just 2.8 percent from 14.2 percent in the old system. The improved information flow enabled experts to analyze data more quickly and accurately, identify children at risk, and provide treatment information to the health staff in the field. Maternal health One of the earliest uses of mobile technology to improve maternal health took place in rural districts of Uganda in the late 1990s. Traditional birth attendants were provided walkie-talkies, allowing them to stay in contact with health centers and obtain advice. An assessment of the program found that it led to roughly a 50 percent reduction in the maternal mortality rate (Musoke 2002). HIV/AIDS In Kenya weekly text messages were sent to AIDS patients to remind them to take their antiretroviral drugs (Lester et al. 2010). Those who received the text messages had significantly higher rates of taking the drugs than those who did not receive them. The study noted that SMS intervention was less expensive than in- person community adherence interventions on the basis of travel costs alone and could theoretically translate into huge health and economic benefits if scaled up. Environment According to one forecast, mobile technology could lower greenhouse gas emissions 2 percent by the year 2020 (GSM Association 2009). This reduction can be met through, among other things, widespread adoption of various mobile-enabled technologies such as smart transportation and logistics, smart grids and meters, smart buildings, and “dematerialization� (replacing the physical movement of goods and services with online transmission). Mobile phones can also be used as tools for environmental monitoring. In Ghana, for example, cab drivers in Accra were outfitted with mobile phones with GPS and a tube containing a carbon monoxide sensor to test pollution levels.b Partnership? MDG target 8F states: “In cooperation with the private sector, make available benefits of new technologies, especially information and communications.� Mobile phone penetration in low-income economies has grown from less than one per 100 people in 2000 to almost one per every three by 2010—largely as a result of private sector investment. Of some 800 telecom projects in developing countries with private sector participa- tion between 1990 and 2009, almost three-quarters involved greenfield operations primarily in mobile teleph- a. “Malawi – Nutritional Surveillance� on the RapidSMS web site: http://www.rapidsms.org/case-studies/malawi-nutritional-surviellence/. b. http://www.globalproblems-globalsolutions-files.org/unf_website/PDF/vodafone/tech_social_change/Environmental_Conservation_case3.pdf c. World Bank and PPIAF, PPI Project Database. http://ppi.worldbank.org. in sectors such as health, education, agriculture, employ- for assessing the development impact of mobile phones. ment, crisis prevention and the environment . . . that The MDGs highlight eight priority areas. Examples of the are helping to improve human development efforts ways mobile phones are being used to address each of around the world� (UNDP 2012). The Millennium the MDGs are given in table 1.2 and throughout this Development Goals (MDGs) provide a useful framework report. Overview 23 Box 1.3 Smartphones and tablets for development The introduction of Box figure 1.3.1 Annotated screenshot of Bangladesh's smartphones and light- Amadeyr Tablet weight tablet comput- ers has revolutionized Menu Volume button the way people access the internet from Speaker mobile devices. These Power powerful touchscreen on/off devices have popular- ized downloadable Back button apps that can do anything from recog- nize a song to turn the Power cord device into a flashlight. Speaker Scaled-down versions of popular office appli- Update button cations for word processing, spread- Source: http://amadeyr.org/en/content/amadeyr-tablets. sheets, and presenta- tions are available for smartphones and tablets as well as ebook software. These devices support internet access over cellular broadband networks and Wi-Fi and often include built-in GPS and still and video cameras. The graphical user interfaces and touchscreens make them ideal for many developing nations particularly those with non-western alphabets and sizable illiterate populations. Smartphone and tablet penetration is rising rapidly in urban areas of developing countries. Several initiatives are under way that feature low-cost tablets and investigate the feasibility of devices for rural areas: • In Bangladesh, the Digits to All (DTA) project distributed custom developed tablets (see screenshot) to over 100 households in a rural village to test their feasibility. The $100 Amadeyr tablet uses the Android operating system with software specifically designed and customized for use by semiliterate, illiterate, and bottom-of-the-pyramid users. The tablet uses a touchscreen operated by seeing pictures and hearing instructions given in Bengali, making it user-friendly for illiterate villagers. The project found that villagers who had never used PCs, let alone the internet, were able to use the tablets within a few days and noted: "It is not the rural population who needs to be trained to have access to information but it is the next generation communication technologies that can be tailored to meet the local needs and be made easily accessible by rural communities" (Quadri et al. 2011). • India launched its locally manufactured Aakash tablet in October 2011(Tuli 2011). Priced at around $35 the tablet is aimed for widespread distribution in schools. Apart from its low cost, the Aakash tablet has other features suitable for the Indian environment including data compression techniques that lower consumption and hence reduce Internet access charges. One of the organizations involved in the project forecasts that some 5 million of the tablets will be shipped in 2012, around half of the equivalent PC figure. (continued next page) 24 Information and Communications for Development 2012 Box 1.3 (continued) • A project in Tanzania has been familiarizing farmers with smartphones to introduce them to the features and potential uses (Banks 2011). Although most farmers already had cell phones, they had never used the internet. The smartphones have been used for geotagging climate information and to make videos of farmers offering advice on techniques. The infor- mation is uploaded to the internet to share with other farmers. The visually oriented infor- mation helped one maize grower to learn from planting mistakes and a few months later he had his first successful harvest. Governments, the private sector, academia, and the development community all have a role to play in promoting smartphones and tablets for development. Governments in particular can be encouraged by the potential of these devices to take ICT for development to another level through easy-to-use graphical interfaces with Internet connectivity over wireless networks. Just as the One Laptop per Child program helped trigger a reduction in low-end computers, a “One Smartphone/Tablet per Citizen� initiative could help generate mass availability. Social networking and democracy ing tools empower people to defend freedom and that Twit- Electronic communication has increasingly become two- ter should be nominated for a Nobel Peace Prize (Gladwell way: examples include participation through feedback in 2010). Others argue that, while these applications make it comments, discussions in forums, and active contribution to easier for people to express themselves, it is “harder for that applications such as Wikipedia or Mozilla. In addition, the expression to have any impact.� In other words, applications tools for users to generate content have been simplified— like Facebook and Twitter make it possible for large not only can most people master text messaging and tweet- numbers of people to voice their opinion, but they do so ing but a growing number can also create social networking virtually, and these tools are not substitutes for physical pages and blogs. Often driven by youth, participation is participation. reaching up the age ladder as these tools and their impact Regardless, recent history has demonstrated that social become publicized and popularized. media along with messages, videos, and pictures sent from The increasing availability of these tools and applications mobile phones are useful tools for organizing protests and on mobile phones is enhancing their popularity. Operators monitoring democracy and freedom. Examples include: in developing countries are working around the limitations of low-end handsets that do not have internet capabilities by • One of the first uses of text messaging for social change providing ways of interacting with social networking appli- took place in the Philippines in January 2001. Political cations through instant messaging, such as MXit in South activists sent SMS text messages urging Filipinos to Africa.19 Safaricom in Kenya offers special SMS functions assemble at Epifanio de los Santos Avenue (EDSA) in allowing users to send and receive Twitter tweets and to Manila to demonstrate for the impeachment of then- update their status and send messages to Facebook.20 president Joseph Estrada. The message, typically The diffusion of mobile phones coupled with social reforwarded by recipients, read: “Go 2 EDSA. Wear networking creates a new space for citizens around the blk.� During the next few days more than a million globe to engage in political action concerning democracy, people showed up and some 7 million SMS were sent. freedom, and human rights. There is disagreement about It is argued that this giant outburst concerned legisla- the extent to which these tools affect appeals for freedom tors, who allowed evidence in the impeachment trial to and democracy. Some observers argue that social network- be presented. By January 20 Estrada had resigned, Overview 25 blaming his exit on the “the text-messaging genera- YouTube to tell the world.�22 Surges in social networking and tion� (Shirky 2011). demonstrations in these countries appear to be connected. All but one demonstration reportedly took place following • Thousands of Moldovans demonstrated against the the initial call to protest on a Facebook page (figure 1.8). The government in the spring of 2009. It was dubbed the number of Facebook users in these countries also grew “Twitter Revolution,� because that application was a main significantly during the demonstrations. method used to organize the demonstrators. One of Similarly, Twitter use increased during the Arab Spring. Twitter’s “Trending Topics� at the time was the tag The #jan25 tag, created to organize the first big protest in “#pman� an abbreviation for Piata Marii Adunari Egypt falling on that day, remained in active use for several Nationale, the main square in downtown Chisinau, the weeks afterward and tag accounted for a majority of Twitter nation’s capital and location of the demonstrations. traffic in Egypt through the resignation of President Hosni Protestors used the local mobile data network to post Mubarak on February 11, 2011. Although there were only tweets from their mobile phones (Morozov 2009). around 130,000 active tweeters in Egypt at the time, the • In Côte d’Ivoire a so-called “web mash-up� site called #jan25 tag had over 1.2 million mentions, illustrating the Wonzomai (“sentential� in the Ivorian Bété dialect) was viral effect of social networking where a tweet can be created to monitor the 2010 presidential election. Users retweeted by many other users. The day Mubarak left office, were provided with telephone number short codes to the number of tweets in Egypt reached its zenith at 35,000. which they could send free SMS and tweets to report During a five-day internet blackout, tweets were sent using abnormalities that they had witnessed during and imme- proxy servers or through contacts in other countries (Zirul- diately after the election. The reports were visualized on a nick 2011). website, which showed the locations where incidents had It is difficult to pinpoint the exact role mobile played in taken place as well as trends plotted over the duration of the uprisings because social networking applications can the election.21 also be used on PCs. In most of the non-Gulf Arab nations, however, mobile ownership far outnumbers computer In the Middle East, mobile has unsettled the region’s possession (figure 1.9a). Further the portability and ease of social and political traditions since the mid-2000s (Ibahrine concealment of mobiles are ideally suited to street protests. 2009). Its greatest impact to date may have come between In addition, camera phones are well integrated with mobile 2010 and 2012 when social media played a role in the “Arab social networking applications, making it relatively simple to Spring� uprisings in Bahrain, Egypt, Libya, the Syrian Arab record and dispatch images and videos over the high-speed Republic, Tunisia, the Republic of Yemen, and other coun- wireless networks available in most Arab nations. In Egypt, tries in the region. As one Egyptian protestor put it: “We use almost 60 percent of mobile owners use their phone to take Facebook to schedule the protests, Twitter to coordinate, and photos or video (figure 1.9b). About 1,000 videos were sent Figure 1.8 Mapping calls for protest on Facebook to actual “Arab Spring� demonstrations, 2011 Yes** Yes Yes No Yes Yes Yes Yes Yes Yes Tunisia Egypt, Arab Yemen, Rep. Syrian Arab Bahrain Libya Oman Saudi Arabia Syrian Arab West Bank and Jan 14 Rep. Feb 3 &10 Republic Feb 14 Feb 17 Mar 3 Mar 11 & 20 Republic Gaza 18.8%* Jan 25 0.93% Feb 14 32.0% 4.3% 7.8% 12.9% Mar 15 and Mar 15 5.5% 1.19% onwards 12.8% 1.67% Source: Dubai School of Government, Arab Social Media Report, May 2011. Note: The percentages underneath each county show Facebook penetration rates at the start of protests. * Facebook penetration rates at the start of protests in each country. ** Initial protest was not organized on Facebook, although further protests were. 26 Information and Communications for Development 2012 Figure 1.9 Mobile phone versus internet access household availability a. Household availability, 2009 b. Mobile phone usage, Egypt, 2011 100 97 95 90 Send text 80 72 80 messages 70 64 64 60 55 Percent Take pictures or 50 58 video 40 30 21 23 20 9 Use the Internet 15 10 3 0 0 20 40 60 80 in a ria t n yp i me a nis Sy hr Eg Ye Tu Ba Mobile phone Internet access Sources: Gallup 2009; Pew Research Center 2011. from cell phones to the Al-Jazeera news organization during this report, in 2009, with a particular focus on mobile appli- the Egyptian protests.23 cations for development. Chapters 2, 3, and 4 have a sectoral Although governments can try to restrict access to the focus on the use of mobile applications in agriculture and internet and mobile networks, they may pay a heavy price. rural development, health, and financial services respec- The Organisation for Economic Co-operation and Develop- tively. Chapters 5 and 6 are cross-cutting, looking at how ment (OECD 2011) estimated that the direct costs to the mobile communications are contributing to entrepreneur- Egyptian government of shutting down the internet and ship and employment and how they are being used to bring mobile phone networks during demonstrations was citizens and government closer together. Finally, chapter 7 $18 million a day, with a much wider economic impact when looks at the shift from narrowband to broadband mobile factoring in industries such as eCommerce, tourism, and busi- networks and the policy implications involved. The Statisti- ness process outsourcing. Restricting access also tends to have cal Appendix provides an overview of recent trends in the a reverse effect: according to a survey of Egyptian and mobile sector and introduces a new analytical tool. The Tunisian citizens, blocking networks causes “people to be more Country Tables at the end of the report provide an at-a- active, [and] decisive and to find ways to be more creative glance view of the status of mobile communications in about communicating and organizing even more� (Dubai World Bank member countries. School of Government 2011). Short of a complete shutdown, users can find workarounds to blocked applications by using Notes proxies; if close enough, they can also pick up cellular signals from neighboring countries. Intriguingly, some of the coun- 1. “[Y]oung people around the world are more immersed in tries identified as having the heaviest internet restrictions were mobile technology than any previous generation.� See Nielsen 2010. also those where social-media-driven demonstrations have 2. http://www.cisco.com/en/US/solutions/collateral/ns341/ taken place (Reporters Without Borders 2009). ns525/ns537/ns705/ns827/white_paper_c11-520862.html. 3. h t t p : / / w w w. s e c . g ov / Arch ive s / e d g a r / d a t a / 1 4 9 8 2 0 9 / Structure of the report 000119312510182561/ds1.htm. 4. A “tweet� is 140 characters (compared to 160 characters for an The rest of this report explores these themes in more detail. SMS). The report distills work carried out by the World Bank 5. For mobile users of Twitter growth in 2010, see http://blog Group and its development partners since the last edition of .twitter.com/2011/03/numbers.html. Overview 27 6. http://blog.twitter.com/2012/03/twitter-turns-six.html. http://www.aspeninstitute.org/sites/default/files/content/docs/ 7. http://trak.in/tags/business/2010/05/24/facebook-twitter- pubs/M-Powering_India.pdf. delhi-police/. Aker, J. 2008. “Does Digital Divide or Provide? The Impact of Cell 8. http://globalvoicesonline.org/2011/01/25/egypt-tweeting- Phones on Grain Markets in Niger.� http://www.cgdev the-day-of-revolution/. .org/doc/experts/Aker%20Cell%20Phone.pdf. 9. http://www.opera.com. Anderson, J., and Kupp, M. 2008. “Serving the Poor: Drivers of 10. “Statistics,� http://newsroom.fb.com/content/default.aspx? Business Model Innovation in Mobile.� info. 10: 5–12. http:// NewsAreaId=22. www.emeraldinsight.com/journals.htm?articleid=1650888& show=abstract. 11. In Korea, games must be reviewed and rated by the Games Ratings Board before they can come on the market. See “‘Big Banks, K. 2011. “From Smart Phones to Smart Farming: Indige- Bang’ of Mobile Games.� JoongAng Daily, May 17, 2011. nous Knowledge Sharing in Tanzania.� National Geographic http://koreajoongangdaily.joinsmsn.com/news/article/arti- News Watch, Nov. 30, 2011. http://newswatch.nationalgeo- cle.aspx?aid=2936279 graphic.com/2011/11/30/smart-phones-meet-smart-farming- indigenous-knowledge-sharing-in-tanzania/. 12. http://www.chinamobileltd.com. Brisson, Z., and K. Krontiris. 2012. “Tunisia: From Revolutions to 13. RIM (Research in Motion). 1999. Annual Report. p. 2. Institutions.� infoDev. http://www.infodev.org/en/Article.814 14. “Research in Motion Reports Third Quarter Results.� Press .html. release. December 16, 2010. http://press.rim.com/financial/. CISCO. 2012. “Cisco Visual Networking Index: Global Mobile 15. Information on the iPhone is adapted from Apple annual Data Traffic Forecast Update, 2011–2016.� http://www.cisco operating reports at http://investor.apple.com/sec.cfm#filings. .com/en/US/solutions/collateral/ns341/ns525/ns537/ns705/ns 16. Apple Inc, 2011 10-K Annual Report, filed Oct. 26, 2011, at: 827/white_paper_c11-520862.html. http://files.shareholder.com/downloads/AAPL/1664072048x0 Dubai School of Government. 2011. “Arab Social Media Report� xS1193125-11-282113/320193/filing.pdf. (May). http://www.dsg.ae/en/ASMR3/. 17. “Nokia and Microsoft Announce Plans for a Broad Strategic Gallup. 2009. “Cell Phones Outpace Internet Access in Middle East.� Partnership to Build a New Global Ecosystem.� Nokia Stock http://www.gallup.com/poll/121652/cell-phones-outpace- Exchange Release, February 11, 2011. internet-access-middle-east.aspx. 18. “News24’s Mobile Site Hits the Half-a-Million Unique Users Gartner Inc. 2012. “Gartner Says Worldwide Smartphone Sales Mark.� Press release, January 20, 2011. http://www.news24.com/ Soared in Fourth Quarter of 2011 with 47 Per Cent Growth.� xArchive/PressReleases/News24-mobile-hits-500-000-users- http://www.gartner.com/it/page.jsp?id=1924314. 20110120. Gladwell, M. 2010. “Small Change: Why the Revolution Will Not 19. http://www.mxit.com. Be Tweeted.� New Yorker (October 4). http://www.newyorker 20. http://www.safaricom.co.ke/index.php?id=1265. .com/reporting/2010/10/04/101004fa_fact_gladwell?current- 21. “Wonzomai: plateforme d’alertes citoyennes pour les élections Page=all. présidentielles en Côte d’Ivoire.� Internet Sans Frontières, Glotz, P., S. Bertschi, and C. Locke, eds. 2005. Thumb Culture: The October 29, 2010. http://www.internetsansfrontieres.com/ Meaning of Mobile Phones for Society. Bielefeld. http://thumb- Wonzomai-plateforme-d-alertes-citoyennes-pour-les-elec culture.loginb.com/. tions-presidentielles-en-Cote-d-Ivoire_a243.html. GSM Association. 2009. “Mobile’s Green Manifesto� (November). 22. http://www.miller-mccune.com/politics/the-cascading- http://www.gsmworld.com/our-work/mobile_planet/ effects-of-the-arab-spring-28575/. mobile_environment/green_manifesto.htm. 23. http://www.guardian.co.uk/world/2011/dec/29/arab-spring- ———. 2011. “Women & Mobile: A Global Opportunity.� captured-on-cameraphones. http://www.vitalwaveconsulting.com/pdf/Women-Mobile.pdf. Ibahrine, M. 2009. “Mobile Communication and Sociopolitical Change in the Arab World.� Quaderns de la Mediterrània no. References 11. http://www.iemed.org/publicacions-en/historic-de-publi- A. T. Kearney. 2011. “The App Frenzy—Just a Short-Lived Fad?� cacions/quaderns-de-la-mediterrania/sumaris/sumari- http://www.atkearney.com/index.php/Publications/the-app- quaderns-de-la-mediterrania-11?set_language=en. frenzyjust-a-short-lived-fad.html. Informa. 2011. “Global SMS Traffic to Reach 8.7 Trillion in 2015.� Adler, R., and M. Uppal, eds. 2008. “mPowering India: Mobile Press release, January 26. http://www.informatm.com/itmg- Communications for Inclusive Growth.� Aspen Institute. content/icoms/whats-new/20017843617.html. 28 Information and Communications for Development 2012 In-Stat. 2011. “Mobile Application Downloads to Approach 48 Portio Research. 2009. “Market Notes: Mobile Games in South Korea.� Billion in 2015.� Press Release, June 7. http://www.instat http://www.portioresearch.com/Market%20Notes%20Mobile% .com/press.asp?ID=3155&sku=IN1104930MCM. 20Games%20In%20South%20Korea.pdf. Jensen, R. 2007. “The Digital Provide: Information (Technology), Puri, J., et al. n.d. “A Study of Connectivity in Millennium Villages Market Performance, and Welfare in the South Indian Fisheries in Africa.� http://www.mobileactive.org/files/file_uploads/ Sector.� Quarterly Journal of Economics 122 (3): 879–924. ICTD2010%20Puri%20et%20al.pdf. doi:10.1162/qjec.122.3.879. http://qje.oxfordjournals.org/ Qiang C., and C. Rossotto. 2009. “Economic Impacts of Broad- content/122/3/879.abstract. band.� In Information and Communication for Development Lane, B., S. Sweet, D. Lewin, J. Sephton, and I. Petini. 2006. The Report: Extending Reach and Increasing Impact, ch. 3. Washing- Economic and Social Benefits of Mobile Services in ton, DC: World Bank. www.worldbank.org/ic4d. Bangladesh. Quadri, A., K. M. Hasan, M. Farhan, E. A. Ali, and A. Ahmed. 2011. Lehdonvirta, V. 2011. “Knowledge Map of the Virtual Economy.� “Next Generation Communication Technologies: Wireless infoDev. http://www.infodev.org/en/Publication.1056.html. Mesh Network For Rural Connectivity.� IEEE Globecom 2011 Workshop on Rural Communications-Technologies, Applica- Lester, R., P. Ritvo, E. Mills, A. Kariri, S. Karanja, M. Chung, J. tions, Strategies and Policies (RuralComm 2011). http://ieeex- William, et al. 2010. “Effects of a Mobile Phone Short plore.ieee.org/xpl/login.jsp?tp=&arnumber=6162331&url= Message Service on Antiretroviral Treatment Adherence in http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp% Kenya (WelTel Kenya1): A Randomised Trial.� The Lancet 3Farnumber%3D6162331. 376, no. 9755 (November): 1838–45. doi:10.1016/S0140- 6736(10)61997-6. http://linkinghub.elsevier.com/retrieve/pii/ Reporters Without Borders. 2009. “Internet Enemies.� http:// S0140673610619976. www.rsf.org/IMG/pdf/Internet_enemies_2009_2_.pdf. Ling, R., and J. Donner, J. 2009. “Mobile Communication.� Sachs, J. 2008. “The Digital War on Poverty.� The Guardian, August http://www.polity.co.uk/book.asp?ref=9780745644134. 21. http://www.guardian.co.uk/commentisfree/2008/aug/21/ digitalmedia.mobilephones. Morozov, E. 2009. “Moldova’s Twitter Revolution.� Foreign Policy, April 7. http://neteffect.foreignpolicy.com/posts/2009/04/07/ Salahuddin, A., H. Baldersheim, and I. Jamil. 2003. “Talking Back! moldovas_twitter_revolution. Empowerment and Mobile Phones in Rural Bangladesh: A Study of the Village Phone Scheme of Grameen Bank.� Musoke, M. 2002. “Maternal Health Care in Uganda: Leveraging Contemporary South Asia 12, no. 3 (September): 327–48. Traditional and Modern Knowledge Systems.� IK Notes, January. doi:10.1080/0958493032000175879. http://www.tandfonline Nielsen. 2010. Mobile Youth around the World. .com/doi/abs/10.1080/0958493032000175879#preview. OECD (Organisation for Economic Co-operation and Develop- Samarajiva, R. 2011. “Challenges of Broadband for Small Pacific ment). 2011. “The Economic Impact of Shutting Down Nations.� Presentation made at launch of Pacific Islands Regu- Internet and Mobile Phone Services in Egypt� (February 4). latory Research Centre, Nov. 10–11. http://www.pirrc.org/ http://www.oecd.org/document/19/0,3746,en_2649_201185 home/index.php?option=com_edocman&task=document.vie _47056659_1_1_1_1,00.html. wdoc&id=6&lang=en. OFTA (Office of the Telecommunications Authority, Hong Kong Shirky, C. 2011. “The Political Power of Social Media.� Foreign SAR, China). 2012. “Key Statistics for Telecommunications in Affairs (February). http://www.foreignaffairs.com/articles/ Hong Kong: Wireless Services.� http://www.ofta.gov.hk/en/ 67038/clay-shirky/the-political-power-of-social-media. datastat/eng_wireless.pdf. TeleGeography Inc. 2012. “International Market Trends.� Opera Software. 2011. “State of the Mobile Web� (April). http:// Presentation at PTC, January 15, 2012. http://www.telegeog www.opera.com/smw/2011/04/. raphy.com/page_attachments/products/website/telecom- Parker, J. 2010. “Rovio: Angry Birds at 60,000 Downloads a Day.� resources/telegeography-presentations/0002/7639/PTC_2012 CNET (August 11). http://reviews.cnet.com/8301-19512_7- _Workshop.pdf. 20013385-233.html. Toto, S. 2011. “How Big Is Japan’s Social Gaming Market?� Febru- Paul, I. 2012. “Android Market Tops 400,000 Apps.� PC World ary 20. http://www.serkantoto.com/2011/02/20/japan-social- (January 4). http://www.pcworld.com/article/247247/android gaming-market-stats/. _market_tops_400000_apps.html. Tuli, S. 2011. “The Internet Revolution: Act 2.� Presentation given Pew Research Center. 2011. “Global Digital Communication: at the World Bank on the Askash tablet, December 8. Texting, Social Networking Popular Worldwide.� http://www http://go.worldbank.org/0RIXUMDMU0. .pewglobal.org/2011/12/20/global-digital-communication- Twaweza. 2010. “CU Tracking School Attendance in Uganda.� texting-social-networking-popular-worldwide/. http://twaweza.org/index.php?i=221. Overview 29 Twitter. 2010. “Measuring Tweets.� Twitter Blog (February 20). Waverman, L., M. Meschi, and M. Fuss. 2005. “The Impact of http://blog.twitter.com/2010/02/measuring-tweets.html. Telecoms on Economic Growth in Developing Countries.� ———. 2011. “200 million Tweets per day.� Twitter Blog (June 30). Vodafone Policy Paper Series 2 (March). http://info. http://blog.twitter.com/2011/06/200-million-tweets-per- worldbank.org/etools/docs/library/152872/Vodafone%20 day.html. Survey.pdf. UNDP (United Nations Development Programme). 2012. “Mobile Williams, M. 2005. “Mobile Networks and Foreign Direct Invest- Technologies and Empowerment: Enhancing Human Devel- ment in Developing Countries.� Vodafone Policy Paper Series. opment through Participation and Innovation.� http://www World Bank. 2011a. ICT in Agriculture eSourcebook. www.ictina .undpegov.org/mgov-primer.html. griculture.org. Van Buskirk, E. 2010. “Five Reasons Cellphones and Mobile VoIP ———. 2011b. World Development Indicators, 2011. http://data Are Forging an Unlikely Truce.� Wired (April 23). http:// .worldbank.org/data-catalog/world-development-indicators. www.wired.com/epicenter/2010/04/mobile-voip-truce/. Zirulnick, A. 2011. “Egypt’s Protests, Told by #Jan25.� http://www Watters, Audrey. 2010. “Just the Facts: Statistics from Twitter .csmonitor.com/World/Global-News/2011/0125/Egypt-s- Chirp.� ReadWriteWeb (April 14). http://www.readwriteweb protests-told-by-Jan25. .com/archives/just_the_facts_statistics_from_twitter_chirp.php. 30 Information and Communications for Development 2012 Chapter 2 Mobilizing the Agricultural Value Chain Naomi J. Halewood and Priya Surya n many developing countries the agricultural sector The mobile revolution in agriculture is not driven by I plays a significant role in the national economy. The sector employs about 40 percent of the total labor force in countries with annual per capita incomes ranging from mobile phones alone. Other mobile devices such as smart- phones and tablets have already begun to have an impact as information delivery channels. These devices can carry $400 to $1,800 (World Bank 2008). Developing countries applications that are much more sophisticated than those will continue to rely heavily on the agricultural sector to available in the basic mobile phone. As the cost of these ensure employment for the rural poor and food security for devices declines, they will increasingly be adopted in devel- growing populations as well as to meet challenges brought oping contexts. on by climate change and spikes in global food prices. This chapter examines how services provided on mobile Improving efficiencies in the agricultural value chain is phones and other mobile devices have begun to change the central to addressing these challenges. Increasing productiv- way stakeholders across the agricultural value chain make ity in agriculture is also critical to reducing poverty. Greater decisions regarding inputs, production, marketing, process- productivity can boost farmers’ income, especially for small- ing, and distribution—decisions that can potentially lead to holder farmers and fishers, who have limited resources to greater efficiencies, reduced transaction costs, and increased leverage in growing and marketing their produce. Creating a incomes. The chapter also examines the key challenges more efficient value chain also requires engaging many mobile service providers are facing in scaling up their oper- stakeholders, from farmers growing crops and raising cattle ations to reach critical mass and to ensure sustainability for to input suppliers to distributors. the development of a whole ecosystem of different stake- The potential benefits of using mobile phones to connect holders. Based on this analysis, the chapter concludes by these diverse stakeholders along the agricultural value chain drawing key policy considerations. speak for themselves. For rural populations, geographically dispersed and isolated from knowledge centers, the informa- Making information mobile tion and communication capabilities of the mobile phone can be even more valuable. Close to 6 billion phones are in Among the numerous technological developments in the use today and are accessible to the 70 percent or so of the information and communication technology (ICT) sector, world’s poor whose main source of income and employment mobile phones have had the most pronounced impact in comes from the agricultural sector (World Bank 2012). developing countries. As detailed in chapter 1, adoption has 31 been driven by improved accessibility and affordability computers have started to revolutionize various entertainment made possible through the expansion of mobile networks and knowledge-based industries such as music, videos, books, that are cheaper to deploy than fiber-optic cable infrastruc- newspapers, and magazines. Combining the operational ture. The capacity or bandwidth available on mobile potential of a computer, the communications capabilities of a networks continues to increase as the technology evolves, phone, and the versatility of a notepad, companies have already enabling more data-intensive services to be delivered started selling no-frills tablets for less than the cost of some through sophisticated devices such as smartphones and mobile phones ($50–$150). tablets. These data-enabled devices, along with their increasing The most common device in developing countries is still affordability, can have a range of implications for the devel- the basic mobile phone, and hence most of the examples opment of mobile applications, including ease of use, richer cited in this chapter are for mobile services provided multimedia that can transform agricultural extension ser- through the text-based SMS (short message service) (see vices, and the ability to access relevant information on table 1.1). An SMS of up to 160 characters can be sent from demand in local languages. While cost may still be a barrier one phone to another. SMS messages can be used to for smallholder farmers,1 community knowledge workers, communicate, inform, and share knowledge on various and local entrepreneurs, users are increasingly able to afford aspects of agricultural and rural life. The SMS function is these mobile devices, incorporating them in their work to generally bundled into the price of a subscription or prepaid collect and disseminate information. Devices targeted for this package; in many, but not all, developing countries, SMS market increasingly use offline technology such as USB costs a small fraction of the price of a voice call and can be (universal serial bus) media to overcome connectivity issues.2 sent asynchronously, that is, without the caller and the called Mobile and remote wireless sensors and identification party having to be online at the same time. Messages sent technologies also have an important role to play in gathering using USSD (Unstructured Supplementary Service Data) data and information relevant to agricultural production, have a functionality similar to instant messaging and can be such as temperature, soil composition, and water levels. used when both parties are online, for instance, to access Illustrative examples of emerging uses of these non-cellular information from a database; USSD messages are sometimes technologies in developing countries are given throughout cheaper than SMS messages. this chapter. As prices continue to decline, data-enabled devices such as Increasingly, specialized mobile services targeted to feature phones, smartphones, and tablet computers are specific agricultural functions are becoming more available expected to become more accessible to more people. These (table 2.1). The basic functions of a mobile phone—sending devices include an operating system, which means they have and receiving voice calls and text messages—are invaluable computing capabilities and can carry software applications, in increasing efficiency in smallholder agriculture by referred to as mobile applications. In the past year tablet improving the flow of information along and between Table 2.1 Mobile-enabled solutions for food and agriculture Improving access to Mobile payment platform Increasing access and affordability of financial services financial services* Micro-insurance system tailored for agricultural purposes Microlending platform Provision of agricultural Mobile information platform Delivering information relevant to farmers, such as agricul- information Farmer helpline tural techniques, commodity prices, and weather forecasts Improving data Smart logistics Optimizing supply-chain management across the sector, visibility for Traceability and tracking system and delivering efficiency improvements for transportation supply-chain efficiency Mobile management of supplier networks logistics Mobile management of distribution networks Enhancing access to Agricultural trading platform Enhancing the link between commodity exchanges traders, markets Agricultural tendering platform buyers, and sellers of agricultural produce Agricultural bartering platform Source: Vodafone 2011. * The role of mobiles in finance is discussed in chapter 4. 32 Information and Communications for Development 2012 various stakeholders in the value chain from producer to A study (Aker 2010) conducted in Niger from 2001 to processor to wholesaler to retailer to consumer. Furthermore, 2006 found that the introduction of mobile phones had mobile phones also enable smallholder farmers to close the reduced grain price dispersion by 6.4 percent and reduced feedback loop by sending information to markets, not just price variation by 12 percent over the course of one year. consuming information from markets. Further, the study notes that the impact (or benefits) of mobile phones tends to be greater in markets that are more remote. Pricing for the agricultural sector requires village- Improved access to agricultural level information and generating relevant localized informa- information tion can be costly and time-consuming. To address this The expansion of mobile networks provides a unique and challenge, and to improve local livelihoods, Grameen AppLab unparalleled opportunity to give rural smallholders access to in Uganda and Reuters Market Light in India (box 2.1) have information that could transform their livelihoods. This collaborated with the government agencies and nongovern- section explores the role of mobile applications in mitigating mental organizations (NGOs) to employ farmers and exten- some of the informational costs that producers in develop- sion service providers to collect information. ing countries face in obtaining better yields, increasing their Feature-enabled phones with camera and GPS (global income, and managing uncertainty. The most common uses positioning system), and smartphones have already begun to of SMS and USSD in the context of agriculture include emerge in rural areas, where they are being used by field access to price information, disease and meteorological workers responsible for collecting data. At volume, the cost information, and information on growing and marketing of data can be much cheaper than SMS in some countries. practices (extension services). For example, through the Grameen Foundation’s partner- ship with a telecommunications operator in Uganda, data is Price information dramatically less expensive than SMS for the volumes their The prevailing market price signals the aggregated Community Knowledge Workers use. A worker can earn $20 demand and value on any given day and fluctuates over a month from disseminating and collecting information and time. Before the expansion of mobile networks, agricul- another $20–$30 from charging farmers’ phones from their tural producers were often unaware of these prices and solar charger. had to rely on information from traders and agents to determine whether, when, where, or for how much to sell Disease and meteorological information their crops. Delays in obtaining this data or misinterpreta- Disease and meteorological information is also required by tion of second-hand pricing information has serious farmers on a frequent basis. Without such information, consequences for agricultural producers, who may end up farmers may be unable to use timely measures to stem losses underselling their products, delivering too little or too from climate shocks and poor yields caused by crop diseases. much of the product, or having their products wither Mobile phones can serve as the backbone for early warning away. Further, reliance on traders or agents creates rent- systems to mitigate these risks and safeguard incomes. seeking opportunities, adding to the agricultural workers’ For example, a publicly funded pilot project in Turkey cost of business. provides locally relevant information to farmers in Kasta- This “information asymmetry� often results in price monu province, where producers maintain orchards dispersion—drastically different prices for the same prod- susceptible to frost and pests (Donovan 2011). Initially, ucts in markets only short distances apart—and thus lost nationally aggregated weather data collected in urban areas income for some farmers and higher prices for consumers. was used but proved to be inaccurate and of limited use to Numerous studies have shown the benefits of ICT in farmers in the provinces, because of differing microclimates promoting access to price information, including increases from farm to farm in temperature, humidity, precipitation, of up to 24 percent in incomes for farmers and up to 57 and soil fertility. Five small meteorological stations and percent for traders and price reductions of around 4 percent 14 small reference farms were then established to collect for consumers depending on the crop, country, and year of data on these variables, enabling accurate pest monitoring. study (table 2.2). Given the wide use of mobile phones with SMS capability, Mobilizing the Agricultural Value Chain 33 Table 2.2 Impact of ICT on farmers, traders, and consumers Location, product, medium Farmer Trader Consumer (study authors) income (%) income (%) savings (%) Comments Uganda, maize, radio +15 Increase in price paid to farmers attributed to (Svensson and Yanagizawa 2009) farmers’ improved bargaining power Peru, range of enterprises, +13 Farm incomes increased, but incomes for public phones (Chong, Galdo, nonfarm enterprises increased more and Torero 2005) India (West Bengal), potatoes, +19 Yet to be published, but both information SMS (M. Torero, IFPRI, pers. through SMS and price ticker boards in markets comm.) shown to be important Philippines, range of crops, +11–17 Commercial farmers, but not subsistence farm- mobile phones (Labonne ers, showed income gains; perceived increase and Chase 2009) in producers’ trust of traders was also reported India (Madhya Pradesh), +1–5 (average: 1.6) Transfer of margin from traders to farmers, soybeans, web-based effect seen shortly after e-Choupal established e-Choupal (Goyal 2008) Sri Lanka, vegetables, SMS +23.4 Appreciable price advantage over control group (Lokanathan and de Silva, pers. over time, plus benefits such as increased comm.) interaction with traders and exploring alternative crop options India (Maharashtra), range of No significant In this one-year study, quantitative analysis did products, SMS (Fafchamps effect not show any overall price benefit, but auction and Minten n.d.) sales in state were thought to affect this finding; price benefits of 9 percent were observed at farm gate sales and among younger farmers Morocco, range of crops, +21 Small sample showed usual behavioral mobile phone (Ilahiane 2007) changes; higher-value enterprises took a more proactive approach to marketing via mobile India (Kerala), fisheries, mobile +8 –4 Outlier in the sense that fish catches are highly phones (Jensen 2007) variable and fishermen have their own boat transport Uganda, range of crops, SMS Bananas +36; Awareness of market conditions and prices and radio (Ferris, Engoru, and beans +16.5; maize offers more active farmers opportunities for Kaganzi 2008) +17; coffee +19 economic gain Niger, grains, mobile phones +29 –3 to –4.5 Traders increased margin by securing higher (Aker 2008) prices through greater capacity to search out better opportunities Ghana, traders, mobile +36 Traders using mobile phones tended to sell at phones (Egyir, Al-Hassan, higher prices but also tended to be larger-scale and Abakah 2010) traders than nonusers Kenya, wholesale traders, +7 Improved trader margin through combination of mobile phones (Okello 2010) cheaper buying prices and higher sale price Ghana, maize, groundnut, and +10 Half of those surveyed receiving market prices cassava, SMS (Subervie 2011) via SMS saw increase in incomes Source: Updated from Dixie and Jayaraman 2011. the project supplies timely information so that producers Information on growing and marketing practices can apply pesticides as and when needed, resulting in lower Information shortfalls exist in many areas throughout the production costs and improved crop yields. Savings agricultural production cycle. Whether for growing crops, amounted to about $2 a tree, with overall savings estimated fishing, or raising livestock, the producer must make deci- to be as much as $1 million a year. Considering the cost sions on cultivating certain crops or livestock, crop inputs, required to set up this service (around $40,000), this project pest management, harvest, postharvest, marketing, and may be viewed as a success. sale. 34 Information and Communications for Development 2012 Box 2.1 How Reuters Market Light generates hyperlocalized information An international news giant launched Reuters Market Light (RML) in 2007 to provide market prices and weather and crop advisory services to farmers in India. Invented by a Reuters employee, this service offers highly customizable market information to farmers through text messages delivered to mobile phones. To subscribe, farmers call a toll-free number to activate the service in the local language and specify the crops and markets in which they have an interest. Farmers receive four to five SMS alerts with relevant information each day. Initial studies show that farmers who receive the service typically gain 5–10 percent more income. RML is one of India’s largest market information services, serving 250,000 customers across tens of thousands of villages. It delivers customized information to India’s farming sector covering over 250 crops, 1,000 markets, and 3,000 weather locations across 13 Indian states in 8 local languages. The company employs over 300 office staff in eight states to process localized agricultural information. The teams, organized according to content type, scour media sources for agri- cultural news (including market prices, pest and disease reports, government programs, weather reports, and local news). This information is sorted by geography and sent to the appropriate subscribers. RML’s growth shows that embracing a wide network of people— including, in this case, price collectors, agricultural institutes, and other information providers—is a vital success factor for mobile applications ecosystems. Such detailed processing can involve large sunk costs with relatively high monthly operat- ing costs of $4 a customer. There is a trade-off between the provision of local information and scalability. Local teams are needed to collect data, and expansion into new areas may involve additional content provision costs, limiting economies of scale. Costs therefore climb in paral- lel with new subscribers. Because it relies solely on income from this single service, RML’s market remains relatively small and is not yet profitable. RML has sought to reach as many customers as possible through a number of strategies, including sales offices in postal offices, local shops, input suppliers, and banks. Customers obtain RML through basic SMS using prepaid scratch cards that give access to the service for a given amount of time. RML competes with traditional information services (radio, market intermediaries, news- papers) and other services that use mobile phones. IFFCO Kisan Sanchar Limited (IKSL) offers similar market information for rural farmers but uses voice messages so illiterate farmers can use the service. Achieving economies of scale is essential for profitability. In 2009 RML report- edly crossed the $1 million sales mark. Sources: Adapted from Donovan 2011 and Qiang et al. 2012. Farming organizations and cooperatives provide farmers supplement and support existing face-to-face trainings for with a broad range of information, as well as institutional farmers and livestock owners. links to large-scale suppliers and distributors. These organi- Smallholder farms are often disadvantaged compared zations give farmers a collective voice and more visibility in with larger enterprises because of their inability to leverage the agricultural value chain. Many of these organizations economies of scale in procuring inputs, marketing their started out by providing information and services through goods, and sharing machinery and knowledge. Successful leaflets, radio, and internet sites, but they are increasingly agricultural cooperatives and farmer groups have solved using the mobile platform to provide tailored information to this problem by enabling small farmers to pool their farmers (box 2.2). These organizations are being used to resources and improve their bargaining power vis-à-vis Mobilizing the Agricultural Value Chain 35 large producers and traders. Cooperatives can also be ideal farmers are less networked, the interventions may need to be networks to launch and manage mobile information serv- more robust—building up social networks to reach the ices, because they can provide highly relevant and localized poorest—and to ensure the information is relevant and information, and drive farmer adoption through existing actionable in order to drive farmer adoption of new tech- social networks. Coopeumo, a Chilean farming cooperative nology services. with fewer than 400 members, uses text messages to help A recent addition to the kind of information available small-scale farmers increase productivity. Through the to farmers is digital images of agricultural land. The Mobile Information Project (MIP), nearly 200 farmers Seeing Is Believing West Africa (SIBWA) project—started receive daily messages including market prices and weather by scientists at the ICRISAT (International Crops Research forecasts directly from the internet to their mobile phones. Institute for the Semi-Arid Tropics)—involves local exten- The MIP provides two different services—DatAgro and Yo sion service providers and farmers in Burkina Faso, Agricultor. DatAgro provides targeted weather updates that Ghana, Mali, and Niger, who interpret information from are particularly useful to farmers at critical points such as very high resolution imagery (VHRI) taken from satellites. planting and harvest. Yo Agricultor is a sophisticated web The images are used to gauge the relative fertility of the portal for farmers supported by the Chilean government soil (through light reflectivity) and to measure the size and that uses MIP to send messages to further its outreach to shape of fields. Many farmers may not know the precise groups that have more limited internet access. The MIP size of their land, so the SIBWA team works with the farm- software works on the basic phones (costing around ers to determine the optimal amounts of fertilizer, pesti- $15–$20) that farmers tend to use and is effective over slow cide, and seeds needed to cover their land evenly. Knowing networks. the size and shape of fields can help rural communities While many farmer groups have seen success in forming plan for future developments, including investments in long-standing cooperatives in Latin America, such coopera- irrigation, for example. The SIBWA team also worked with tives are less prevalent in Sub-Saharan Africa. Organizations local NGOs with expertise in specialized technologies and serving them, and companies operating in the value chain, extension services to complement their efforts (Deloitte thus face different needs and opportunities. In areas where 2012). Box 2.2 A pregnant pause for Sri Lanka’s cows The Information and Communication Technology Agency (ICTA) of Sri Lanka discovered that between 2003 and 2008, more than half of the country’s 560,000 milk cows were not in fact pregnant at any given time, resulting in a loss of 30–35 days’ worth of milk. Low pregnancy rates resulted from a lack of timely access to artificial insemination and breeding services. The eDairy program was introduced in 2009 to enable farmers to request veterinary and extension services (related to issues such as animal health, artificial insemination, milk prices, and construction of dairy stalls) through a simple SMS interface or on touchscreen tablets. Farm- ers type in their personal identification code and the code of the service they need. The request is then sent to all registered suppliers, so they can contact the farmers directly. Farm- ers usually obtain feedback within a few hours. So far, 300 farmers have registered for the service. According to Sri Lanka’s Department of Dairy Foods, milk production could be increased by 30 percent if artificial insemination services were requested and supplied in a timely manner. Moreover, the ICTA estimates that farmers could earn an additional $262 per calf each year. Source: Adapted from Qiang et al. 2012. 36 Information and Communications for Development 2012 Improving data visibility for emerged from the IPO48 competition, a 48-hour boot-camp value-chain efficiency event aimed at giving mobile and web developers a platform to launch their applications. Besides the staple text-based In addition to improved information services for producers, service for obtaining price information, M-Farm enables mobile services can also enable better access to markets and suppliers to publicize information on special offers to farm- other value-chain stakeholders such as traders, input suppli- ers. This format follows a global trend in deal-of-the-day ers, and end users. Mobiles can help agribusiness companies websites that feature discounted offers at local retailers, such and wholesale buyers connect with geographically dispersed as the Groupon service in the United States. producers. This section explores how mobiles and mobile applications create value in the value chain by linking Tracing products from farm gate to market producers to distributors and retailers through better The growing globalized and interdependent nature of food record-keeping and traceability. production and distribution, combined with raised aware- ness of food-borne diseases, has shed light on the need to Improving logistics ensure food safety in the global food supply chain.5 These Transporting produce requires coordination between trends have catalyzed effective technological innovation to producers, truckers, and, at times, warehouse owners and trace the food supply from point of origin to the consumer aggregate traders. Many producers, especially in remote and (Karippacheril, Rios, and Srivastava 2011) rural areas, must carry their produce themselves, often by The International Organization for Standardization foot, to the nearest collection point. Coordinating trans- (ISO) defines traceability as the ability to trace the history portation is also key to larger traders who aggregate produce or location of the item or product under consideration. for sale in urban areas or for export. Studies show that so far Traceability is therefore a common element of both public traders are using their websites to relay information on and private systems for monitoring compliance (with regu- transport and logistics. Some of these services, however, lations on quality environmental, or other product or could also be provided on a mobile phone. process attributes related to food). Traceability is becoming The Zambia National Farmers Union operates an SMS- increasingly relevant to developing countries that want to based information service that provides information on gain or expand into new export markets. Smallholder commodity prices to farmers. To complement the service, farms, which often lack resources to keep up with strict and the union has also launched an electronic transport system changing food safety standards on their own, are now that allows registered transporters to publicize the arrival increasingly turning to cooperatives and aggregators who and delivery times of loads or cargo.3 They have three main are leveraging ICTs to improve traceability. By opening up services, one through which producers can publicize the size new specialized market opportunities, the use of ICTs has of their load and where it is located for pickup, the second led to improved consumer protection and food safety on for transporters on the way back from the market with an the one hand, and better livelihood outcomes for farmers empty truck that could potentially be used to haul products on the other (box 2.3). from the market to the village, and the third a directory of For this challenge, radio frequency identification (RFID) transporters that allows producers to contact a transporter chips are emerging as a solution for traceability. Placed on a directly. This service is being provided through a website in crate of apples or in the ear of a cow, the chip can collect data Zambia, but in Morocco, a similar service is using mobile such as motion, temperature, spoilage, density, light, and phones. Through the use of voice and SMS, farmers coordi- other environmental variables though an interface with nated with local truckers to improve product transport and wireless sensor networks. Traceability systems for bulk prod- identify where to deliver their products. Some farmers devel- ucts have been implemented in developing countries, even oped a two-way trade, bringing products back from the among small farmers. market to sell in their own rural communities (Dixie and Representing more than 500,000 small farmers, the Jayaraman 2011). National Coffee Growers association in Colombia has Another example is M-Farm Ltd,4 an agribusiness leveraged RFID technology to improve traceability and company established by a group of women developers, that recordkeeping on coffee quality standards. At a cost of Mobilizing the Agricultural Value Chain 37 Box 2.3 Tracking specialty coffee Lack of traceability during the growing and procurement process is a major constraint for producers growing for high-value export markets, such as specialty coffee. For the coopera- tives and companies that manage the exports, emerging mobile technology—smartphones and tablets—can play a major role in capturing, tracking, and accessing valuable information from growing practices to crop quality. Sustainable Harvest is a coffee importer that works with 200,000 farmers in Latin America and East Africa. Extending its relationship-based procurement model to the digital platform, the organization and its farmer training offices have introduced a new coffee traceability program—called the Relationship Information Tracking System, or RITS—to help coffee grow- ers become more efficient, reliable, and quality-focused through a new mobile or tablet-based information tracking system. RITS provides farmer cooperatives with the ability to trace each step of the value chain. Using a cloud-based application, the cooperative managers can record deliveries of coffee from each member including details of coffee varieties and quality scores for each lot of coffee received. The application also tracks the certification status of each delivery, processes farmer payment, and generates reports on farmer productivity, payments, and samples. Roaster clients can access videos, photos, quality, and lot information from their supplier cooperatives. The application has been designed for Apple’s iPad and iPhone, but it can be used in any smartphone through the web browser. Devices with large touchscreens allow for easier input of a large variety of information. The application can record information offline, and then upload to the online database when connectivity is restored. In 2011 Sustainable Harvest also launched RITS Ed, an iPad app that delivers agricultural training videos on organic coffee production and quality control that co-op managers can use to assist their members. Sustainable Harvest also plans to expedite the application process for third-party certification (organic, for example) through the launch of a new module, RITS Metrics, that will enable more robust, and customizable reports. RITS is currently testing the program with two cooperatives in Peru with 500 members and one cooperative in East Africa with 1,840 members. Sources: USAID 2011; http://www.sustainableharvest.com/; Annerose 2010. $0.25 a tag, encased wear-resistant tags with unique farm the control, risk management, and eradication of bovine identification numbers are distributed to farmers. These diseases such as foot-and-mouth disease. The use of RFIDs tags are read at each step to market, thus helping to main- to replace traditional paper-based recording, has increased tain the stringent standards required for this high-value the accuracy of the data and the speed with which it is specialty coffee.6 disseminated. It has also contributed to a more vigorous RFID chips are also commonly used to trace animal market: the Namibian livestock market increased approxi- movements, enabling the monitoring of animals from cradle mately $83 million in 2010 (Deloitte 2012). to grave. The Namibian Livestock Identification and Trace- Mali is a landlocked country with 80 percent of employ- ability System (NamLITS) (Collins 2004), implemented in ment in subsistence agriculture and fishing. In the 1990s the 2005, focuses on nurturing livestock production for export government identified mangoes as having potential for markets. More than 85 percent of agricultural land in diversifying the country’s exports. It faced a number of chal- Namibia is used to raise livestock, and beef production lenges, however, including meeting increasingly stringent constitutes 87 percent of agricultural revenue. The objective criteria regarding the origin of products, the way they are of NamLITS is to implement a traceability system to help in grown, the fertilizers and pesticides used, and how they are 38 Information and Communications for Development 2012 packed. With the support of donors and NGOs, Fruit et found that as remote communities in Uganda were provided Legumes du Mali (Fruilema), an association representing with access to a mobile network, the share of bananas sold 790 small producers and five exporting companies, launched rose from 50 to 69 percent of the crop. This effect, however, a web- and mobile-enabled platform through which poten- was not observed for maize, which is a less perishable crop. tial buyers can track and monitor their mangoes (Annerose Improved understanding of real-time market dynamics 2010). The consumer can type the number shown on a tag can help farmers deal with external demand, such as switch- attached to the fruit into a website to get the exact details of ing to high-demand but riskier (perishable) products (Sen where the mango came from, its producer, and the methods and Choudhary 2011). Risky products include crops that are used to cultivate the mango. To leverage the mobile phone easily ruined if the rainy season arrives too early, for exam- platform, Fruilema partnered with a Senegalese mobile ple. The growing sophistication and knowledge of value operator, Manobi, to pay farmers an additional 9 cents a chains also means that farmers can work directly with larger pound when they entered data on their produce on the intermediaries, capturing more of the product’s value. Manobi website. One of the key challenges Fruilema faces is Farmers are able to expand their networks and establish to make sure farmers send in all the necessary information contacts directly with other buyers in other areas (Shaffril et to meet the criteria for exporting (Deloitte 2012). al. 2009). Aside from the overall impact of mobile phones on marketing and market linkages, certain mobile applications can help aggregate information between buyers and sellers Enhancing access to markets (box 2.4). Mobile phones, although owned and used by individuals, As mobile service and applications providers in agricul- can nevertheless have an important impact in linking ture become more knowledgeable about the needs of the markets and key stages of the value chain. A recent study of farmers as well as their behavior, they are developing farmers conducted in Bangladesh, China, India, and increasingly sophisticated applications. In 2000 ITC (Indian Vietnam found that 80 percent of farmers in these countries Tobacco Company), a large conglomerate in India, broke owned a mobile phone and used them to connect with new ground by establishing e-Choupal—kiosks with agents and traders to estimate market demand and the sell- computers—in rural villages, where farmers are able to ing price (Minten, Reardon, and Chen n.d.). More than access price, planting, and weather information. Since then, 50 percent of these farmers would make arrangements for the company has been working to provide its services over sale over the phone. Another study (Muto and Yamano 2009) mobile phones. ITC has been piloting a new virtual Box 2.4 DrumNet, the value chain on your mobile phone More than two-thirds of Africans rely on agriculture for a living, yet because of the lack of complete information, high transaction costs, and inefficient value chains, farmers, intermedi- aries, and buyers are unable to effectively collaborate in the fragmented market. Pride Africa’s DrumNet project is an integrated platform that uses various ICTs, including mobile phones, to provide producers, traders, and financial service providers with an end-to-end solution to procuring inputs, linking to buyers, and finalizing credit and payments. Starting with fast-growing horticulture and oilseed industries in Kenya, DrumNet ran a series of pilots that delivered services to agro-buyers, banks, farm input retailers, and farmers. The pilots were implemented in five different Kenyan provinces and are reported to have involved over 4,000 small-scale farmers. Before farmers plant crops, DrumNet’s network of entrepreneurs negotiates contractual arrangements between buyers and farmers. These agreements allow farmers to access credit (continued next page) Mobilizing the Agricultural Value Chain 39 Box 2.4 (continued) from partner institutions such as Equity Bank and to purchase inputs from certified retailers. At harvest, DrumNet franchise representatives coordinate produce aggregation, grading, and transportation through agreements with local field agents and transporters. DrumNet tracks and facilitates the entire process through the use of complimentary manual and SMS applications. Benefits to the stakeholders include: • Farmers reduce transaction costs by accessing both credit and markets through DrumNet and are able to pay off their loans with their farm produce proceeds. Farmer income is reported to have risen by an average of 32 percent. • Large-scale buyers are freed from the requirement of managing cumbersome transactions to ensure reliable supplies of produce from multiple smallholders. • Input sellers can access new customers without having to sell products on credit. • Banks and microfinancial institutions are able to tap into a currently inaccessible market for savings and credit while avoiding high transaction costs. The process creates an enabling environment for agricultural finance in a number of ways: • Banks are assured at the time of lending that farmers have a market for their produce and the means to adequately serve that market, which indicates a healthy revenue stream. • Banks offer in-kind credit to farmers for inputs. • Cashless payment transfers reduce strategic default, since farmers cannot obtain revenue until their outstanding loans are fully paid. The DrumNet project employs tested value-chain approaches to promote agricultural lend- ing. Its operating cost of about $6.80 a user is high, and DrumNet is facing difficulties because it has not yet reached a critical mass that would allow it to stand alone without donor funding. Farmers’ inability to attain sufficient crop yields, because of irregular and insufficient rain and other factors, has also threatened the success of the project. Sources: Adapted from Deloitte 2012, Qiang et al. 2012; and http://www.prideafrica.com. commodity exchange, Tradersnet, that enables the direct price cannot suffice. Therefore, Esoko became a mobile purchase and sale of coffee by producers and wholesale and web-enabled repository of current market prices and purchasers over an internet-based trading platform. SMS a platform to enable buyers and sellers to make offers and messages are sent to users’ mobile phones every morning connect to one another. Using a bronze/silver/gold/plat- with the offers and grades available for purchase on that day. inum subscription model, Esoko has also been able to At the end of the day, users receive a text message with details offer differentiated service to a diverse customer base. In a of what actually took place (Vodafone 2009). recent study of 600 smallholder farmers in northern In Ghana, TradeNet established Esoko to serve as a Ghana, the French National Institute for National central repository of price information to be run by a Research (INRA) found that farmers have seen a 10 centralized agency such as the government. The people percent revenue increase since they began receiving and who set up Esoko soon realized that the agricultural sector using Esoko SMS market prices (Egyir, al-Hassan, and consists of many decentralized markets where a single Abakah 2010).7 40 Information and Communications for Development 2012 Policy considerations • Supporting infrastructure. To make the more powerful mobile devices, such as smartphones and tablets, more The examples provided in this chapter demonstrate that accessible and affordable, governments will need to food producers and intermediaries are already able to do ensure that the private sector is capable of offering more with their mobile phones to raise farm incomes and mobile broadband services at affordable prices. That the efficiency of the value chain. Governments have a role to requires an enabling environment where competition play in ensuring that innovation in this area continues. An between telecommunications providers is robust. enabling environment for mobile services, applications, and other devices, such as RFIDs and remote sensors, includes In addition to supporting the emergence and growth of three support pillars: the mobile services industry, governments could also benefit from the data generated through mobile phone networks • Business models. Many of the services described in this and remote sensors. For example, information on price, chapter rely on public funding and are in pilot stages. weather, and diseases could potentially be aggregated so that DrumNet and RML, while they provide robust business research institutions and relevant government agencies can models, are still figuring out how to address high per-user analyze and monitor trends. The highly relevant and up-to- costs, by either scaling up or adding new services to date information generated from this type of analysis can increase the number of subscribers. Public funding, inform higher-level policy dialogue on topics such as applied through pull mechanisms and results-based commodity pricing, subsidy effectiveness, climate change, financial incentives such as challenge funds, can provide and trade. Further, by disclosing the aggregated data and grants and soft loans to innovators who are experiment- analysis to the public, people who initially provided the data, ing with new technologies and business models until they such as farmers, input suppliers, and distributors, would can become financially viable. The public sector can also benefit from the analysis—an important component of the innovate in its own agricultural programs to create more Open Data Initiative that many developing countries are client-oriented information and knowledge services that implementing. leverage mobile technology. Finally, governments can play a catalytic role in facilitating collaboration and dialogue between various private sector players, public Conclusions sector service providers, and academia and knowledge As information becomes more accessible through the use of centers. mobile devices for stakeholders throughout the agriculture • ICT skills. Information needs in developing countries are value chain, people are gradually moving toward more effi- highly localized; therefore, nurturing a domestic ICT cient ways of producing agricultural products, increasing skills base in the workforce is crucial to the development incomes, and capturing more value by linking fragmented of mobile applications and services in the agricultural markets. Key benefits include increases in productivity and space. Several of the examples cited in this chapter are income for farmers and efficiency improvements in aggre- from India and Kenya, where the strong presence of gating and transporting products. Although elements of the skilled software professionals and entrepreneurs has mobile agriculture platform are emerging in developing significantly helped these countries lead in producing countries, the full potential has yet to be realized. The mobile relevant and high-quality development-focused applica- services cited here are simply tools, and without the proper tion services. Governments have a critical role to play in supporting pillars such as those described above, the key ensuring that the education curricula at the secondary, challenges that hamper their sustainability will be difficult to tertiary, and vocational levels properly reflect the needs of overcome. the emerging digital economy. In addition to the pull- Looking forward, governments will need to examine their based mechanisms and challenge funds described above, role in creating an enabling environment for innovators seek- technology hubs and technology incubation programs ing ways to meet the needs of this information-intensive can have a crucial role in encouraging entrepreneurship sector. Specific ICT strategies for the agriculture sector would and emergence of an industry in this space. help guide both the public and private sector in creating this Mobilizing the Agricultural Value Chain 41 enabling environment. These policies should take into Working Paper 535. Inter-American Development Bank, Wash- account the need for new business models in specific country ington, DC. http://www.iadb.org/res/publications/pubfiles/ pubwp-535.pdf. contexts and facilitate inputs such as the supporting infra- structure (broadband services) and the IT industry (IT skills). Collins, J. 2004. “African Beef Gets Tracked: Namibia Beef Track- ing by Savi Technologies.� RFID Journal, December 10. Technologists, governments, NGOs, private businesses, and http://www.rfidjournal.com/article/articleprint/1281/-1/1/. donor agencies are just starting to work together to leverage Deloitte. 2012. “Agriculture Sector Report.� In Transformation- mobile technologies for greater inclusion of rural and poor Ready: The Strategic Application of Information and Communi- communities into their spheres of activity. cation Technologies in Africa. World Bank and African Development Bank. http://www.etransformafrica.org/sector/ agriculture. Notes Dixie, G., and N. Jayaraman. 2011. “Strengthening Agricultural 1. The definition of smallholder varies across countries and Marketing with ICT.� Module 9 in ICT in Agriculture regions but generally refers to farmers with limited volumes of e-Sourcebook. World Bank, Washington, DC. http://www.ict yield and low or uncertain income. According to the Food and inagriculture.org/ictinag/sourcebook/module-9-strength Agriculture Organization (FAO 2004), smallholder farmers ening-agricultural-marketing. often cultivate less than one hectare of land in favorable areas, Donovan, K. 2011. “Anytime, Anywhere: Mobile Devices and Serv- whereas they may cultivate 10 hectares or more in semi-arid ices and Their Impact on Agriculture and Rural Development.� areas, or manage 10 head of livestock. Module 3 in ICT in Agriculture e-Sourcebook. http://www.icti 2. Examples are the new tablets from the Canadian firm nagriculture.org/ictinag/sites/ictinagriculture.org/files/final_ Datawind, which have been much in demand in emerging Module3.pdf. markets such as India, Turkey, and Thailand. http://www.bbc Egyir, I. S., R. al-Hassan, and J. K. Abakah. 2010. “The Effect of .co.uk/news/technology-17218655. ICT-Based Market Information Services on the Performance 3. http://www.znfu.org.zm/index.php?option=com_wrapper of Agricultural Markets: Experiences from Ghana.� Unpub- &view=wrapper&Itemid=89. lished draft report, University of Ghana, Legon. 4. http://afrinnovator.com/blog/2010/11/02/video-pitch-of- ———. 2011. “ICT-based Market Information Services Show ipo48-winner-m-farm. Modest Gains in Ghana’s Food Commodity Markets.� Paper 5. The main source for this section is Karippacheril, Rios, and presented at a conference on Development on the Margin, Srivastava 2011. University of Bonn, October 5–7. 6. Colombia Coffee: “Finalists Unveiled for the Fourth Annual Fafchamps, M., and B. Minten. n.d. “Impact of SMS-Based Agricul- RFID Journal Awards,� RFID Journal, March 18, 2010, http:// tural Information on Indian Farmers.� Unpublished draft report. www.rfidjournal.com/article/view/7467. FAO (Food and Agriculture Organization). 2004. “Framework for 7. http://www.esoko.com/about/news.htm. Analyzing Impacts of Globalization on Smallholders.� Rome. http://www.fao.org/docrep/007/y5784e/y5784e02.htm. Ferris, S., P. Engoru, and E. Kaganzi. 2008. “Making Market Infor- References mation Services Work Better for the Poor in Uganda.� CAPRi Aker, J. C. 2008. “Does Digital Divide or Provide? The Impact of Working Paper 77. World Bank, CGIAR Systemwide Program Mobile phones on Grain Markets in Niger.� Working Paper on Collective Action and Property Rights, Washington, DC. 154. Center for Global Development, Washington, DC. http://www.capri.cgiar.org/pdf/capriwp77.pdf. http://www.cgdev.org/content/publications/detail/894410. Goyal, A. 2008. “Information Technology and Rural Markets: ———. 2010. “Information from Markets Near and Far: Mobile Theory and Evidence from a Unique Intervention in Central Phones and Agricultural Markets in Niger.� American Economic India.� University of Maryland. Journal: Applied Economics 2 (3): 46–59. http://ideas.repec.org/ Ilahiane, H. 2007. “Impacts of Information and Communication a/aea/aejapp/v2y2010i3p46-59.html. Technologies in Agriculture: Farmers and Mobile Phones in Annerose, D. 2010. “Manobi: ICT for Social and Economic Devel- Morocco.� Paper presented at the Annual Meetings of the Amer- opment.� Presentation to the World Bank, Washington, DC, ican Anthropological Association, December 1, Washington, DC. August 12. Jensen, R. 2007. “The Digital Provide: Information (Technology), Chong, A., V. Galdo, and M. Torero. 2005. “Does Privatization Market Performance, and Welfare in the South Indian Fisheries Deliver? Access to Telephone Services and Household Income in Sector.� Quarterly Journal of Economics 122 (3): 879–924. Poor Rural Areas Using a Quasi-Natural Experiment in Peru.� http://qje.oxfordjournals.org/content/122/3/879.abstract. 42 Information and Communications for Development 2012 Karippacheril, T. G., L. D. Rios, and L. Srivastava. 2011. “Global Recipe for Success.� European Journal of Scientific Research 36 markets, Global Challenges: Improving Food Safety and Trace- (1): 41–48. http://www.eurojournals.com/ejsr_36_1_05.pdf. ability While Empowering Smallholders through ICT.� Module 12 Subervie, J. 2011. “Evaluation of the Impact of a Ghanian-based in ICT in Agriculture e-Sourcebook. World Bank, Washington, DC. MIS on the First Few Users Using a Quasi-Experimental http://www.ictinagriculture.org/ictinag/sites/ictinagri Design.� INRA (French National Institute for National culture.org/files/final_Module12.pdf. Research). http://www.esoko.com/about/news/pressreleases/ Labonne, J., and R. S. Chase. 2009. “The Power of Information: 2011_15_12_Esoko_INRA.pdf. The Impact of Mobile Phones on Farmers’ Welfare in the Svensson, J., and D. Yanagizawa. 2009. “Getting Prices Right: The Philippines.� Policy Research Working Paper 4996, World Impact of the Market Information Service in Uganda.� Journal Bank, Washington, DC. http://papers.ssrn.com/sol3/papers of the European Economic Association 7 (2–3): 435–45. .cfm?abstract_id=1435202##. http://onlinelibrary.wiley.com/doi/10.1162/JEEA.2009.7. Minten B., T. Reardon, and K. Chen. n.d. “The Quiet Revolution of 2-3.435/abstract. ‘Traditional’ Agricultural Value Chains in Asia: Evidence from USAID (U.S. Agency for International Development). 2011. Staple Food Value to Four Mega-cities.� Unpublished draft, Sustainable Harvest. ICT and Agriculture Profile. http:// International Food Policy Research Institute, Washington, DC. microlinks.kdid.org/sites/microlinks/files/resource/files/ Muto, M., and T. Yamano. 2009. “The Impact of Mobile Phone SustainableHarvestProfile.pdf. Coverage Expansion on Market Participation: Panel Data Vodafone. 2009. “India: The Impact of Mobile Phones.� http:// Evidence from Uganda.� World Development 37 (12): 1887–96. www.icrier.org/pdf/public_policy19jan09.pdf. http://www.sciencedirect.com/science/article/pii/S0305750X0 ———. 2011. “Connected Agriculture: The Role of Mobile in 9000965. Driving Efficiency and Sustainability in the Food and Agri- Okello, J. 2010. “Effect of ICT-based MIS Projects and the Use of culture Value Chain.� http://www.vodafone.com/content/ ICT Tools and Services on Transaction Costs and Market dam/vodafone/about/sustainability/2011/pdf/connected_ Performance: The Case of Kenya.� Unpublished draft. agriculture.pdf. Qiang, C. Z., S. C. Kuek, A. Dymond, and S. Esselaar. 2012. Mobile World Bank. 2008. World Development Report 2008: Agriculture in Applications for Agriculture and Rural Development. World Bank. Development. Washington, DC. http://siteresources.world- http://go.worldbank.org/YJPDV8U9L0. bank.org/INTWDR2008/Resources/WDR_00_book.pdf. Sen, S., and V. Choudhary. 2011. “ICT Applications in Agricultural ———. 2011. ICT in Agriculture eSourcebook. www.ictinagricul Risk Management.� Module 11 in ICT in Agriculture e-Source- ture.org. book. World Bank, Washington, DC. www.ICTinAgriculture.org. World Bank. 2012. “World Development Indicators on Agriculture Shaffril, H. A. M, M. S. Hassan, M. A. Hassan, and J. L. D’Silva. and Rural Development.� http://data.worldbank.org/topic/ 2009. “Agro-Based Industry, Mobile Phone and Youth: A agriculture-and-rural-development. Mobilizing the Agricultural Value Chain 43 Chapter 3 mHealth Nicolas Friederici, Carol Hullin, and Masatake Yamamichi alling a doctor is a natural response to getting sick services that move health care away from pure public service C in most of the developed world, but that is not always an option in many developing countries. The spread of mobile phones in developing nations promises delivery toward seeing the patient as a consumer. Mobile health software and services have proved to be versatile tools for collecting data at the point of action, potentially result- to change that, however, by enabling health professionals to ing in more accountable management of information in speak directly with their patients, to arrange health care health care delivery, increasingly going beyond telemedi- services such as appointments, and to monitor symptoms. cine.2 Table 3.1 summarizes some of the more important This chapter is concerned with what happens once mHealth categories. basic communications are widely available. How can mobile devices be used to enhance health care? How can Why mHealth? Opportunities and mobile devices improve the efficiency and effectiveness of challenges health care interactions between patients and immediate health care providers (such as doctors and hospitals), as How can mobile communications help to achieve public and well as between patients, providers, and other institutions private health sector objectives, and what policies can help involved with health (such as health information portals, facilitate mHealth deployments? On the supply side, mobile insurance companies, and government agencies)? communications can help provide health care services more Early on, the term mHealth was narrowly defined to quickly and cheaply in many cases, mainly by focusing on mean wireless telemedicine involving the use of mobile primary, preventive, and self-empowered approaches to telecommunications and multimedia technologies and their health care. From the demand perspective, mobile phones integration with mobile health care delivery systems can make it easier and more convenient not only to find rele- (Istepanian and Lacal 2003).1 However, this definition does vant information quickly but also to enter health data and not do justice to the wide variety of stakeholders and types engage in interactive services, such as symptom tracking and of uses that mHealth spans today. In this report, a broader online communities of patients. definition is adopted: “mHealth encompasses any use of For mHealth to deliver, mHealth application developers mobile technology to address health care challenges such as should ideally consult with medical or health informati- access, quality, affordability, matching of resources, and cians trained to understand the information flows behavioral norms [through] the exchange of information� involved in health care processes.3 At the same time, to (Qiang et al. 2012). It is a dynamic field for innovative new reach a wider market and to achieve sustainability, many 45 46 Table 3.1 Major categories of mHealth services and applications mHealth category Typical fields of application Description/use cases Examples (and sources) Improving management and • Treatment of medical conditions • Remote patient tracking • Moca (Celi et al. 2009) decision-making by health care • Prescriptions • Updating and verification of digital • 104 Mobile (see box 3.3) professionals • Targeted provision of information and medical records, accessible to health marketing about health care productsa care providers and pharmacists • Delivery of health insurance and savings products Real-time and location-based • Health care delivery and logistics • Monitoring and surveillance of disease • RapidSMS in Somalia (Vital Wave data gathering • Crisis mapping outbreaks for more timely reporting of Consulting 2011) and Ethiopia • Resource allocation symptoms and containment of (see box 3.2) epidemics • Trilogy/International Federation in Haiti • Crisis mapping after natural disasters (Qiang et al. 2012) • Reporting of urgent health needs • Desert Medicine Research Centre • Real-time provision with information on Interactive Voice Response System available health facilities and resources in India (Chalga et al. 2011) • Supply chain management • Access to health emergency services and rapid response systems Provision of health care to remote • Remote provision of health care • Medical advice, reminders counseling, • Remote mobile health care for rural and difficult-to-serve locations services monitoring, simple diagnoses communities in Sri Lanka (Perera 2009) • Extending the reach of health care • Focusing on areas where only limited • Moca (Celi et al. 2009) • Complementing traditional face-to-face physical infrastructure is available, such health care services as remote and rural areas, including telenursing, teleradiology, telepsychiatry, and tele-education. Fostering learning and knowledge • Medical knowledge repositories • Retrieving best practices, international • RAFT network in Burkina Faso, Côte exchange among health professionals • Virtual communities standards, and patient histories from d’Ivoire, Mali, and Senegal (Vital Wave • Event and conference organization other health care professionals Consulting 2011)b • Local communities • Moca (Celi et al. 2009) • Expert crowdsourcing for health information wikis • Virtual classrooms, webinars, and the like Promoting public health • Delivery of health information • Games, quizzes, and other nontradi- • Text to Change in Uganda • Awareness building and campaigning tional mechanisms (Vital Wave Consulting 2011) • (Mass-oriented) tele-education • Conventional mHealth prevention and education campaigns • Medication reminders Improving accountability • Transparency for usage of funds • Public health fund flow tracking • Kgonfalo (see table 3.2), Botswana— • Feedback systems • Interactive portals for comments and UPenn Partnership (2012) complaints • Transparency International in Northern Ugandac Self-management of patient health • Enabling better self-help and limiting • Patients obtain accurate information • MEDAfrica (see box 3.1) transactions • Patients can better understand their • Calorie Counter (popular • Lowering health care costs (shifting diagnoses, for example, by checking downloadable app)d tasks to the patient) medical records • Patient empowerment • Mainly focused on noncommunicable diseases and may deal with health indicators such as weight and blood pressure a. See Patil (2011) for suggestions on how to integrate traditional product marketing concepts, as well as social marketing, into mHealth for developing countries. b. RAFT (Réseau en Afrique Francophone pour la Télémédecine) http://www.who.int/workforcealliance/members_partners/member_list/hugraft/en/index.html. c. http://www.ict4democracy.org/about/partnerproject-briefs/ti/. d. The “Calorie Counter: Diet and Activities� was one of the 10 most popular Apple iPhone/iPad apps in 2011; see http://mobihealthnews.com/15229/top-10-iphone-medical-apps-for-2011/7/. 47 mHealth applications need to offer standardized services texting has probably been the most prominent mode of that can be delivered and accessed by nonexperts. Finally, delivery (see table 3.1 and box 3.2), perhaps, according to mHealth should be integrated with larger eHealth some research, because texting is already an integral part programs and aligned with the delivery of offline health of mobile usage culture (Gombachika and Monawe 2011). care services (box 3.1). So far, short message service (SMS) Increasingly, however, mHealth services are also offered as Box 3.1 Kenya: A breeding ground for mHealth applications Box figure 3.1.1 MedAfrica app Kenya has emerged as a leading player in mobile for development, largely because of the success of the mPesa mobile payment ecosystem, based on local application developers, projects mounted by local nongovernmental organiza- tions (NGOs), favorable governmental policies, foreign investment, and stable economic condi- tions. This active ecosystem has benefited the health sector, with many mHealth applications being piloted in Kenya. Unfortunately, the proliferation of pilot programs, with diverse goals and stakehold- ers, has fragmented the Kenyan mHealth landscape: standardized platforms that are well-integrated with the local health care system are lacking; few projects have been endowed with long-term funding; and systematic evaluation and impact studies are scarce. Only recently have more streamlined coordination and division of responsibilities started to emerge. Increasingly, the govern- ment is taking over mHealth implementation and ensuring that it complements national policy, while NGOs undertake research, monitoring, and evaluation. Kenya certainly offers an insightful repertoire of mHealth applications. A recent notable effort is MEDAfrica.org, a company launched in November 2011 that is currently being incubated in the infoDev mobile applications lab in Nairobi (see chapter 5). The application inte- grates symptom checkers, first-aid information, doctor and hospital directories, and alert services into a single, customizable mobile information platform (see screenshot in this box). MEDAfrica won the East African application contest Pivot 25. MEDAfrica is also pioneering a viable business model, which has attracted worldwide media and investor attention. Other Kenyan mHealth applications are based on remote moni- toring or supply chain management through simple SMS technology. Examples include systems for HIV medication reminders, children’s health monitoring, early-infant HIV diagno- sis, and medicine validation through scratch codes. Sources: Adapted from Qiang et al. 2012 and www.medafrica.org. 48 Information and Communications for Development 2012 Box 3.2 Ethiopia: SMS helps in monitoring UNICEF’s food supply chain Box figure 3.2.1 RapidSMS in Ethiopia Ethiopia faces significant challenges to effective performance in its health sector. The country is struggling to reduce maternal and child mortality, preventable communicable diseases, and malnutrition. While some policy initiatives have achieved notable success, Ethiopia is likely to meet only one of the six health-related targets under the Millennium Development Goals (MDGs) by 2015. Health care coordination, monitoring, and supply chain management are largely deficient. Funding is limited and well-trained health staff scarce. In 2008 Ethiopia was hit by severe droughts, leading UNICEF to administer a large-scale food distribution program. Because of the country’s poor telecommunication infrastructure and low technical literacy, however, inventory management at local distribution centers was arduous: teams of monitors had to travel back and forth to the centers to deliver hand- written reports of inventory. Inventory analysis could be started only after the data had been delivered, which often took several weeks. In response, UNICEF worked with RapidSMS, which helped cut delays in data transmission related to paper-based collection. Transmission times were reduced from about two months to approximately two minutes. Additionally, data quality discrepancies decreased from 14.2 percent to 2.8 percent while generating significant cost savings. In developing RapidSMS, UNICEF has shown that mHealth appli- cations can represent a feasible low-tech response to challenging conditions such as those in Ethiopia. RapidSMS was designed to be a simple supply chain management tool, which auto- matically integrates inventory information sent by SMS into a central database in real time. SMS technology is easily accessible and robust, and minimal training is needed to use the application. RapidSMS allows for stock taking, new admissions, precise location of distri- bution centers, and analysis of the quantities of food distributed and consumed. This analy- sis was sped up by immediate visualizations in graphs and maps, accessible by offices in all locations. Monitors still have to travel to distribution centers, but from there they can immediately send stock information to the server. Saving days in travel literally saves lives: UNICEF can respond to shortages and deliver new food resources more promptly, rapidly, and efficiently. The RapidSMS system is a success story, but several issues arose, including a lack of standards for coding distribution centers, poor allocation of responsibilities, and slow reso- lution of technical issues. This experience underlines the need for ICT systems to be inte- grated into existing health care systems as well as the need for capacity building to use ICT effectively. Source: Adapted from Vital Wave Consulting 2011. mHealth 49 voice-based systems (Chalga et al. 2011) or as specific from the developed world but must be designed to applications that can be downloaded to a mobile device, as match the scarcity of resources both on the demand and the MEDAfrica example in box 3.1 illustrates. supply side. Optimism about the potential of mHealth is growing; • Privacy and security concerns. Typically, mHealth faces indeed, its potential to be a cost-effective solution for health significant privacy and security concerns, with limita- care in developing countries has led to a growing influx of tions on access to patient data that can complicate inter- funds, mainly from public sector and civil society donors actions between different systems such as primary care, (Vital Wave Consulting 2011). In turn, the funding is scat- emergency care, and insurance. tered and mHealth implementations are too often stand- alone pilot programs. Further, mHealth can help consumers • Limited evidence. Reliable assessments on the impact of and communities in the developing world keep themselves mHealth services are scarce, making it difficult to justify informed and take more control of their health choices.4 The adoption and implementation. opportunities that mobile phones offer for health monitoring • Difficult coordination of stakeholders. Orchestrating could mean that people will start thinking of their phones as diverse private, public, and development sector interests personal digital assistants (PDAs) to take care of their health. for mHealth can be challenging. Clear roles have yet to be In parallel, entry barriers for the supply of applications are defined, and role models are lacking. The different stake- often lower for mHealth than for other eHealth services or holders have different goals and strategies that often over- conventional delivery of health care, because small start-ups lap and conflict, leading to frictions and inefficiencies. and local developers can develop mobile software with rela- tively few resources and can address a much wider potential • Interoperability issues. Piecemeal implementation of user base. The shift from eHealth to mHealth can also create mHealth products and services has led to a lack of inter- an opportunity for a shift from top-down to bottom-up operability between applications that run on different approaches, from government to consumer initiatives, devices and platforms. and from centralized to decentralized spending, if mHealth initiatives are effectively implemented. The potential of mHealth However, the health sector remains both complex and challenging. The most relevant challenges to the greater Despite the growing popularity of mHealth, in both usage uptake of mHealth include: and commercial terms, there is a disappointing lack of comprehensive studies evaluating its impact. Overall, • Insufficient financial resources. Obstacles to comprehensive mHealth is often associated with lower costs and improve- mHealth solutions are often financial, especially in the ments in the quality of health care, but also with a focus on developing world. In particular, if no payment structures the prevention of diseases and promotion of healthy have been established, it is unclear who should cover the lifestyles. In line with this assertion, a recent study estimates costs for mHealth in private health care (consumers, that mHealth reduces data collection costs by approximately governments, insurance companies?). This is critical, since 24 percent, costs of elderly care by 25 percent, and maternal the largest part of the cost is often related not to the devel- and perinatal mortality by 30 percent (Telenor Group 2012). opment of the mHealth application but to the integration The same study finds that mHealth can improve compliance of mHealth services with other health care infrastructure. with tuberculosis treatment by 30–70 percent. • Lack of sustainable business models. The roll-out of Given consumers’ higher purchasing power and their mHealth and other eHealth products and services needs shown willingness to pay for mHealth applications and sustainable business models and revenues. Besides a lack devices (IBM Institute for Business Value 2010; Mobi- of public and private investments in developing such HealthNews 2009), huge business opportunities have been products and services, low-income countries often lack identified, mainly in the developed world. Of note, in 2011 human resources and purchasing power on the demand the third convention of the mHealth Summit attracted side. Thus, business models cannot simply be adapted more than 3,600 visitors, up from fewer than 800 in 2009 50 Information and Communications for Development 2012 (mHealth Alliance 2011), and the mHealth market went up translate into a greater scope for mHealth solutions; it is from $718 million in 2011 to an estimated $1.3 billion in expected that major emerging economies, finding them- 2012 in the United States alone (Telecoms Tech 2012). In selves in rapid transition to new health care structures, will particular, mHealth applications aimed at individuals are see the strongest uptake of mHealth in the years to come growing in popularity. The number of health-related appli- (Freng et al. 2011). Because of the diversity of mHealth cations in Apple’s App Store grew from just over 4,000 in applications and the limited potential of mHealth commer- February 2010 to more than 15,000 by September 2011; cialization, however, the larger economic or development roughly 60 percent of these were aimed directly at impact of mHealth is difficult to assess, and there is a lack of consumers, with the most popular applications relating to systematic data for the developing world that would justify cardio workouts and diet (figure 3.1). The most popular higher-level investments (Qiang et al. 2012). health-related search in 2011 was for information on Nonetheless, more than 500 mHealth projects have chlamydia, a sexually transmitted disease, suggesting that been deployed around the world (Telenor Group 2012). the privacy offered by mobile access to health information According to the World Health Organization’s Global is important to users. Also the use of “wellness apps� is seen Observatory for eHealth (GOe), some 83 percent of 112 to be growing: an estimated 30 percent of smartphone users surveyed countries had at least one mHealth program in are likely to use them by 2015 (Telenor Group 2012). operation, with the majority reporting at least four types Currently, applications focusing on individuals are mainly of application (WHO 2011). The same survey showed that geared to developed countries, where purchasing power and the mHealth adoption gap between low- and high-income education are higher. countries is fairly small: 77 percent of the former and 87 Yet, mHealth arguably offers even greater potential in the percent of the latter reported they had implemented at developing world, where mobile phones serve not only as least one mHealth program. In absolute terms, Africa is communication tools but also as key means for accessing still the region with the most countries with mHealth health information, obtaining medical insurance, and deployments, while the developed world and other devel- making payments. As long as macroeconomic conditions are oping regions have seen stronger adoption growth in at least somewhat favorable, a lack of existing structures can recent years (figure 3.2). Figure 3.1 Relative popularity of consumer health applications in Apple’s App Store, 2011 PHR 0.71% Medication adherence 1.36% Smoking cessation 2.23% Emergency 2.73% Cardio 16.36% Sleep 4.13% Chronic conditions 5.45% Mental health 5.80% Other 15.36% Calculator 6.03% Strength training 6.97% Women’s health 7.27% Diet 14.15% Stress and relaxation 11.44% Source: MobiHealthNews 2011. Note: PHR = personal health records. mHealth 51 Figure 3.2 Number of countries with at least one Figure 3.3 mHealth ecosystem mHealth deployment, by World Bank region Government Legislators Health 90 Regulators Health system 80 3 Legal system 6 Health care workers Ministries Medical supply chains 70 7 Patients 9 60 Countries 50 14 mHealth Health 40 applications funding mHealth Finance 30 29 service Banks Technology delivery 20 Insurance companies Software Private investors 10 16 developers Philanthropists Mobile Mobile 0 Donors operators platforms Individual Handset 03 04 05 06 07 08 09 10 11 users/house- 20 20 20 20 20 20 20 20 20 makers holds Europe and Central Asia South Asia East Asia and Pacific Middle East and North Africa Latin America and Caribbean Sub-Saharan Africa Source: Qiang et al. 2012. Developed countries Source: Adapted from GSMA mHealth Tracker 2012. Business models for mHealth Basing mHealth services on a sustainable business model is The mHealth ecosystem vital for implementing mHealth. The first decision that an The emergence of mHealth initiatives in many parts of the mHealth organization has to make is what financing model to world can make it difficult to assess their impact in a adopt. Broadly, the options are nonprofit, for-profit, or hybrid. coherent manner. Increasingly, mHealth stakeholders are • Nonprofit organizations may rely less on investments from realizing the need to arrive at a more holistic understand- the private sector and more on large blocks of funding ing of the subject not only to base implementation on best from ministries, multilaterals, and other major donors. practices but also to factor in local circumstances. More- Often, a nonprofit mHealth organization’s goal is not over, the large number of different stakeholder groups revenue maximization, but maximum development requires that their different roles and responsibilities be impact and improvement of patients’ health outcomes. clarified as well. Because mHealth always exists within and • In contrast, for-profit organizations focus on developing interacts with a country’s larger health care system, it will services and products that generate revenues to be be affected by public policy, private sector influence, distributed to investors and owners, although they may diverse patient needs, and the interests of several other also include a philanthropic element, for example, in participants. probing the opportunities in new markets. A useful framework for the mHealth ecosystem is provided in a World Bank report on mobiles in health • Whereas health care almost always implies strong public (Qiang et al. 2012), which positions mHealth at the sector involvement, there is certainly potential in nexus of health, technology, and financial services, with mHealth for for-profit projects as well, suggesting that government influencing all three of these spheres (figure hybrid models may be an appropriate option. For 3.3). This positioning is in line with a common argu- instance, a subscription to mDhil’s medical information ment that mobile financial services can enhance the service in India, costs 1 rupee ($0.02) a day, which is in impact of mHealth initiatives (mHealth Alliance and line with the purchasing power of its target consumers— WEF 2011). young Indians between 18 and 25 (Qiang et al. 2012). 52 Information and Communications for Development 2012 For both nonprofits and for-profits, clear value proposi- Principles for implementing mHealth tions for the still emerging mHealth industry have yet to be applications established. Value chains in mHealth can be complicated Clearly, the field of mHealth is just beginning to demon- even for simple applications (Vital Wave Consulting 2009), strate its full potential. So far, there have been many pilot so capturing and monetizing value for only one among many projects and scattered initiatives, with dramatically varying stakeholders in the chain can be difficult (Freng et al. 2011). levels of success (table 3.2). This section briefly outlines Because demand for mobile applications for health care some of the principles that hold across contexts from these delivery is high, however, consumers might be willing to pay early mHealth initiatives.5 for mHealth, for instance, if the service can help them avoid disease and the high opportunity costs of suffering from a Avoid a one-size-fits-all approach medical condition. Cumulative losses in global economic Mobile health applications must be designed to respond to output from noncommunicable diseases are expected to people’s needs and suited to their local context. A common amount to $47 trillion, or 5 percent of GDP, by 2030, so pitfall is that, once an application is working well technically governments also have an interest in promoting better access and is seen to have high potential, there is an immediate to health information (Chand 2012). enthusiasm to implement it everywhere regardless of For now, however, the main challenge for the mHealth context. Conducting readiness assessments with users can industry in low-income countries has been to continue to help avoid such overextension. Close involvement of health deliver services once initial funding of pilot projects ends practitioners in the design and development of mobile app and to scale up or replicate effective models in large-scale content can also ensure accuracy for public health programs. implementations. This challenge results in part from a A good example of successful adaptation to various contexts lack of long-term feasible business models. In developed and sectors is RapidSMS—this system has been used for countries, many mobile apps are offered free of charge, food supply chain management in Ethiopia (see box 3.2), as with revenues derived from advertising. Fee-for-services a citizen outreach system in Senegal (see table 3.2), and as an is a secondary model (for example, some health apps in emergency response tool in Somalia (Vital Wave Consulting Apple’s App Store cost up to $79). To obtain sustainable 2011). The success of RapidSMS has also sparked the devel- investment in this emerging industry, the private sector opment of other mHealth tools, such as ChildCount+ (Vital needs to demonstrate effective and robust mobile apps Wave Consulting 2011). that address both local and national health needs, espe- cially for low- and middle-income countries, where aver- Maintain flexibility age per-user revenues are lower. In cases where incentives Policy-makers must be careful not to overregulate mHealth for the private sector are not strong enough (that is, nor to prescribe, from the top down, how applications are to where the market prospects are too uncertain, or be implemented. Because mHealth technology is cheap to consumers lack purchasing power), the public sector will implement and change, it can be a tool for achieving effi- have to fill the gap, for example, by directly subsidizing ciencies and improved flexibility in the health system. mHealth services, limiting administrative cost for licens- Mobile health can also be combined with other mobile ser- ing, or engaging in public-private partnerships. vices to enhance its impact. The industry may also evolve The business models for mHealth must follow the actual freely, including in ways that the health sector may not antic- health care needs of individuals and the public to be ipate. For example, mHealth and mMoney can be integrated sustainable. As health is considered a public good, the busi- in a variety of useful ways. A patient might receive a ness models should also be aligned with public policy inter- prescription through an mHealth application and pay for it ventions. Investment in mobile applications for public using an mMoney transfer or bank account, all using the health issues such as noncommunicable diseases should same mobile phone. Health care workers who spend most of help reduce the costs of health care services and guarantee a their time in the field and transfer information to health healthier population and workforce for developing systems through mobile phones could receive their wages in economies. the same way. mHealth 53 54 Table 3.2 Selected examples of mHealth projects and lessons learned Country Application Services provided Scale/location Key success factors and lessons learned Botswana Kgonafalo: A remote diag- Initially focused on oral health, it now Initially piloted in 6 locations, The initial implementation, using technology from a nosis facility using camera- covers radiology, cervical cancer, and it is now ready to be scaled Bangladeshi company, was not robust, and was Botswana-UPenn equipped mobile handsets dermatology. Photos sent from rural up to 25 locations, before replaced by an application developed locally by PING Partnership (2012) and tablets to send photos areas are used to determine whether going nationwide, with fund- (Positive Innovation for the Next Generation). In of patients for treatment to transport patients for treatment in ing from the government. addition, handsets were replaced with Android Tablet advice. Gaborone. The pilot program assessed PCs preloaded with medical databases and treatment 230 cases over a 6-month guidelines. Kenya Changamka MicroHealth: Smart cards are available (from Launched in 2008, it now This health application is designed to be user friendly Changamka (2012) A smart card that enables supermarkets and the like) to outpa- covers 18 service distributors and to respond to selected high-demand services. payments to be made for tients and pregnant mothers. and 29 health care facilitators Improved interoperability has created value, especially medical services via mPesa, Patients can buy health care pack- across Kenya but is mainly in linking many different service providers and linking health care providers ages that include consultation, lab concentrated in Nairobi. insurance companies. with medical insurance test, and drugs, for example, or top Available to all citizens. companies. up credit with amounts as low as K Sh 100 ($1.20). Peru WaWaRed: A mobile appli- SMS messages and basic health Launched in 2010, WaWaRed Involvement of pregnant mothers has been facilitated WawaRed (2012) cation providing timely information delivered at different is available in Ventanilla by a high adoption rate of mobile phones. messages for pregnant stages during pregnancy. It also Distrito, a vulnerable commu- This case has also highlighted that fathers need to be women. includes a symptom checker, which nity of Lima, and serves the involved in maternal health education for effective can be accessed and used via SMS. Callao community of 5,000 communication with health care providers. people. It is now being scaled up nationally. Chile Centro de Informatica en Providing health information to and Launched in 2011 to serve An assessment of digital literacy among the elderly Centro de Salud: Provision of health from mobile devices, such as phones 3,000 elderly people in the was carried out before the project launch. Informatica en care to the elderly at home, and tablets, Devices store electronic Pedro Aguire Cedra district, it Awareness raising and training is essential to engage Salud (2012) in a project called Cuidado health records to facilitate care at is now being scaled up effectively with health care services when using Domiciliario. home. nationally. mobiles for health care at home. Senegal RapidSMS: Implementation Citizen engagement with health care Launched in mid-2009, the Significant costs have been saved by using SMS RapidSMS (2012) in Senegal through the providers through an SMS aggrega- Jokko initiative now serves aggregation to broadcast text messages to multiple Jokko initiative, with UNICEF tion service, allowing short texts to 800 communities in 8 African recipients for the price of a single message. and Tostan, an NGO. be distributed to a large network of countries. The messaging process may take up to 8 hours users. depending on the technology used, so it may not be effective for emergency alerts. South Africa Cell-Life Aftercare: an SMS Patients receive SMS alerts when Begun in 2001 as a research In South Africa, the prevalence of HIV and AIDS in Cell-Life (2012) alert service for patients medication is due, along with other project at the University of adults is close to 20 percent. Cell-Life has developed following HIV retroviral health tips. Mobile phones are also Cape Town, this initiative a philosophy of “Dispense, Communicate, Capture.� therapy. used for data capture by nurses became a company in 2005. following patients. It is currently working in partnership with over 50 organizations. Sources: Assembled from diverse sources (see References). Take standards and interoperability into account EpiHandy program in Uganda, the IHISM system in Although apps should be adapted to local context, designing Botswana, and the Dokoza system in South Africa (Vital a separate and incompatible application for every stake- Wave Consulting 2011). Accordingly, it is estimated that holder group or every locale frequently leads to large ineffi- mHealth can double the number of rural patients reached by ciencies. Applications often benefit from economies of scale a physician (Telenor Group 2012). and reach—the power of singular mHealth services can be Poor evaluation of current information systems before multiplied by their ability to work together, operate on entering the digital arena may result in fragmented or inap- common platforms, and share information. Making interop- propriate health care applications. For example, it is vital for erability a prerequisite for new mHealth applications could mHealth applications to be interoperational with eGovern- help reduce inefficiency or duplication. Accordingly, a lack ment applications in other sectors. A success story in this of standards is seen as preventing the scaling up of applica- context is Rwanda, which has implemented an overarching tions and, thus, to be a key obstacle to achieving cost savings eHealth initiative combining patient record tracking, trans- through mHealth (Telenor Group 2012). The perspective missible disease monitoring, and supply chain management, should go beyond the health sector: seamless integration as well as mHealth telemedicine apps for health profession- with other mobile platforms, such as mobile money, can als in remote areas (Vital Wave Consulting 2011). enhance the value of mHealth applications even more. A push for more universal platforms can come from the Track key success indicators for monitoring and top (for instance, as part of a national eHealth strategy evaluation that encompasses mHealth) or from the bottom (espe- The need for evaluation does not end once an mHealth cially at the point of care through mobile phones). The application has been implemented. To move from pilot proj- greatest value will be realized when both strategies are ects to full-scale implementation, evidence is needed on the used and complement each other. International standards impact of mHealth applications, along with identification of for hardware and software platforms can ensure interoper- operational efficiencies and detailed estimates of cost ability among mHealth applications and other mobile savings. In short, monitoring and evaluation (including tools, while also enabling the development of locally rele- tracking project-specific success indicators) are necessary vant applications. International bodies such as the right from the beginning of an mHealth implementation. mHealth Alliance, the Health Metrics Network, and the However, only 7 percent of low-and lower-middle income Continua Health Alliance are helping to forge cooperation countries report that they evaluate their mHealth initia- in the development of globally recognized standards and tives (WHO 2011), and only a few systematic analyses of metrics. For example, to achieve seamless exchange of data nongovernmental projects exist. A rare exception is WelTel elements, HL7 and ISO standards have been widely used (Lester et al. 2010), an SMS-based tool for tracking for electronic health records. Standards and interoperabil- compliance with antiretroviral therapy. Peer-reviewed ity must be addressed early on—consolidating many frag- evidence confirmed its positive influence on health mented or incompatible services is hard, as cases like outcomes beyond the initial stages, which, in turn, led to Kenya (see box 3.1) or Ethiopia (see box 3.2) have shown. the continuation of funding for the project and its increased sustainability. Evaluate existing information systems Multiple health information systems exist and data are gath- Ensure quality and content of health information ered with or without mobile applications. Reliable assess- The content and quality of health information must be ments of these systems are useful to identify where mHealth tailored to end users and decision-makers. Lack of trust is a is needed and how it can best be implemented. Evaluation of major resistance factor against the use of mobile delivery flows of health services should also be taken into applications in health care provision. Similarly, local consideration. Mobile apps may prove complementary to languages and cultures often represent major barriers to existing solutions, especially for remote data collection and adoption. One notable example of the relevance of trust in telemedicine—for example, in the cases of the Health health information is the Indian mobile platform mDhil. Management and Research Institute in India (box 3.3), the While it received significant private sector investment and mHealth 55 Box 3.3 India: Health Management and Research Institute—104 Mobile India’s Health Management and Research Institute (HMRI) is a public-private partnership between the state government of Andhra Pradesh (which bears 95 percent of costs) and the Satyam Foundation (which bears 5 percent of costs) based in Hyderabad, Andhra Pradesh. HMRI launched “104 Mobile� in 2008a to improve local health services by replacing the tradi- tional health care system with mHealth applications for disease surveillance, prevention coun- seling, telemedicine, and supply chain management. 104 Mobile sends medical units (MUs) to habitations more than three kilometers away from the nearest public health service provider to provide medical care to rural populations. Each MU circulates on a fixed date every month, ensuring continuity of care. Maternal and child health are prioritized, along with the diagnosis and management of chronic diseases such as diabetes, hypertension, asthma, and epilepsy. 104 Mobile deployed 475 MUs to 22 districts throughout Andhra Pradesh. Generally, treatments at clinics tend to be costly, and more than half of unmet requests for outpatient care could be treated by phone in rural areas—a poten- tial that 104 Mobile can exploit through its hotline for medical consultations. HMRI has delivered the following major benefits (partly thanks to the integration of mHealth applications): • Expanded the service area covered by 25 percent • Services may cost as little as one-tenth of those provided by the government • Up to 55 percent of 600,000 unmet requests for outpatient treatment could be treated by phone • 1.26 million pregnant women each received an average of three antenatal care check-ups • 2.9 million people with chronic diseases were screened, tested, and provided with medication • Over 10 million unique electronic health records were established, making this one of the largest public electronic health record databases worldwide Source: Qiang et al. 2012. a. 104 Mobile has been transitioned back to the government of Andhra Pradesh and the service is currently operated by the Ministry of Health under the government. was able to attract a fairly large base of paying customers, and personal data, especially in the case of infectious and one of its biggest challenges was to establish credibility and transmissible diseases. For example, the privacy and confi- win the trust of its users, given the inaccuracy and lack of dentiality of personal data of patients is vital to prevent clarity of much of the health information it had to draw on discrimination in the workplace. The dangers of poor privacy (Qiang et al. 2012). requirements are often visible only after the damage is done (for example, once security leaks are exploited by hackers), Respect privacy and confidentiality making this a natural field for government intervention and Although awareness of the issue of data privacy is often low regulation (Qiang et al. 2012). However, privacy regulation in developing countries, the case can be made that mecha- should be limited according to context. For instance, health nisms guaranteeing some level of privacy and confidentiality records on nonstigmatizing infectious diseases (such as dengue are a universal requirement for mHealth. Evidence from fever) should be shared quickly and widely, while a patient’s developed economies shows that privacy and confidentiality interests in the confidentiality of personal data might triumph, are important success factors in the management of public for example, in cases of sexually transmitted diseases. 56 Information and Communications for Development 2012 Enable public-private partnerships the information being conveyed corresponds to best prac- Policy-makers contemplating mHealth should consider tices and health system priorities. bringing private sector stakeholders to the table. If admin- istered wisely, public investment and technology partner- Ensure the commitment of leaders ships enriched with competitive incentives (through The mHealth industry is today at a pivotal moment in its tenders and challenges, for example) can improve the qual- rapid evolution. To realize the industry’s full potential for ity of mHealth apps and services and improve choice. improving health outcomes, long-term leadership is needed Often, public-private partnerships (PPPs) can benefit from from government and from the health, technology, and a division of labor based on the respective competencies financial sectors. Their leadership will help supply the and resources of the stakeholders. For instance, private industry with better inputs—both tangible (such as handset mobile operators and software developers might be better technology and financing) and intangible (such as market situated to provide the technological platform and develop regulations, standardization of software, and rules for using the mHealth applications, while governments can provide a bandwidth). It will also ensure that mHealth services corre- favorable regulatory environment and integration with the spond to health sector priorities. The impact of committed existing (public) health care system (Qiang et al. 2012). leadership can be magnified by a series of multipliers— Governments might also use a PPP approach to spark inno- improvements in reach, affordability, quality assurance, vation from a more agile private sector. This approach behavioral norms, and matching of resources—that can seems to be very effective; the largest and most scalable boost health outcomes. High-level leadership within mHealth initiatives are mostly supported by PPPs (WHO government is especially crucial for forging inter-ministry 2011). One notable project is ChildCount+: the Kenyan partnerships. government, the Millennium Villages Project, and UNICEF collaborated with Zain and Sony Ericsson as technology Conclusions partners to develop a monitoring and tracking system with a focus on easily treatable diseases; the new system is As this chapter has argued, mHealth applications have the expected to dramatically reduce child and maternal mortal- potential to transform health care systems in low-income ity (Qiang et al. 2012). economies: mHealth can generate cost savings and provide more effective health care delivery within rela- Offer training and take literacy into account tively limited resources. Modern forms of health care are Mobile health services will have a greater impact on health at a tipping point where consumers are taking on more outcomes where their users have high levels of literacy (and responsibility for managing their own health choices, and for health workers, training) in ICT and health. Proficiency mobile phones could contribute greatly to this shift of with mobile devices and computers saves time and reduces decision-making from state and health institutions to the errors. As a result, during mHealth implementation, the individual. However, the most substantial challenge for technical literacy of users needs to be factored in, and staff mHealth is the establishment of viable and sustainable have to be trained to use the necessary technology. In addi- business models that can be replicated and scaled up. One tion, training in technical and organizational skills is often step forward could be clearer delineation of roles within needed to launch, scale, and sustain mHealth interven- the health ecosystem between public and private health tions. For instance, major barriers to adoption of telemed- care providers. Accordingly, for “macro�-focused public icine in Uganda were lack of knowledge and skills on the health purposes, the World Health Organization (WHO part of health care staff (Isabalija et al. 2011). There are 2005) recommends that mHealth be integrated into a many ways to achieve improvements in these areas: dedi- country’s broader eHealth strategy. Finally, a missing cated training institutions, public information campaigns, component is the effective monitoring and evaluation of programs in schools, and even software for mobile devices mHealth, which could inform the design of more success- that trains people in their use and in treatment methods. ful mHealth applications at this critical stage of their All of these may ultimately require oversight to ensure that development. mHealth 57 Notes Behavior in Malawi.� Journal of Health Informatics in Develop- ing Countries 5 (2). 1. One of the first uses of the term mHealth was in 2008 when the Rockefeller Foundation engaged global eHealth experts at GSMA mHealth Tracker. 2012. http://apps.wirelessintelligence Bellagio, Italy; see Mishra and Singh (2008). .com/health/tracker/. 2. For a comprehensive review on the provision of telemedicine Health Management and Research Institute. 2012. “Our Work, in the developing world, see Wooton et al. (2009). Mobile Health Services.� Hyderabad, India. http://www.hmri .in/104-Mobile.aspx. 3. Medical informatics professionals are trained in medicine and computer sciences and information theory. See www.imia.org IBM Institute for Business Value. 2010. “The Future of Connected for more details. Health Devices.� http://public.dhe.ibm.com/common/ssi/ecm/ en/gbe03398usen/GBE03398USEN.PDF. 4. The role of social intermediaries, including civil society organizations and community-based organizations, should Isabalija, S. R., K. G. Mayoka, A. S. Rwahana, and V. W. Mbarika. not be overlooked. They can focus on health workers, build- 2011. “Factors Affecting Adoption, Implementation and ing their capacity and training them in ICT skills. In addition, Sustainability of Telemedicine Information Systems in Uganda.� they can offer help directly to citizens in poor and isolated Journal of Health Informatics in Developing Countries 5 (2). communities who do not possess adequate ICT skills, for Istepanian, R. S. H., and J. Lacal. 2003. “Emerging Mobile Commu- instance by timely provision of necessary information to nication Technologies for Health: Some Imperative Notes on minimize information asymmetries, and sometimes by MHealth.� Proceedings of the 25th Institute of Electrical and providing training on how to use mobile applications. Electronics Engineers Annual International Conference: Engi- 5. We also refer readers to a more detailed list of Calls to Action, neering in Medicine and Biology Society, Cancun Mexico. divided by stakeholders, in Vital Wave Consulting (2009). Lester, R., et al. 2010. “Effects of a Mobile Phone Short Message Service on Antiretroviral Treatment Adherence in Kenya (WelTel Kenya1): A Randomised Trial.� The Lancet 376 (9755): References 1838–45. mHealth Alliance. 2011. “2011 mHealth Summit Attracted Indus- Botswana-UPenn Partnership. 2012. http://www.med.upenn.edu/ try Leaders from Around the Globe.� December 13. http:// botswana/. www.mhealthsummit.org/pdf/mhs11_wrap_release.pdf. Celi, L., L. Sarmenta, J. Rotberg, A. Marcelo, and G. Clifford. mHealth Alliance and WEF (World Economic Forum). 2011. 2009. “Mobile Care (Moca) for Remote Diagnosis and “Amplifying the Impact: Examining the Intersection of Mobile Screening.� Journal of Health Informatics in Developing Health and Mobile Finance.� http://www.mhealthalliance.org/ Countries 3 (1): 17–21. news/making-connection-between-mobile-health-and- Cell-Life. 2012. http://www.cell-life.org/home. mobile-finance. Centro de Informatica en Salud. 2012. http://www.centrodeinfor- Mishra, S., and I. P. Singh. 2008. “mHealth: A Developing Country maticaensalud.org/?page_id=24. Perspective.� http://www.ehealth-connection.org/files/conf-mate Chalga, M. S., A. K. Dixit, B. Shah, and A. S. Bhati. 2011. “Real rials/mHealth_%20A%20Developing%20Country%20 Time Health Informatics System for Early Detection and Perspective_0.pdf. Monitoring of Malaria in Desert District.� Jaisalmer, India. MobiHealthNews. 2009. “Wireless Health: State of the Industry 2009 Journal of Health Informatics in Developing Countries 5 (2). Year End Report.� http://mobihealthnews.com/wp-content/ Chand, S. 2012. “Silent Killer, Economic Opportunity: Rethinking Reports/2009StateoftheIndustry.pdf. Non-Communicable Disease.� Chatham House briefing paper ———. 2011. “Consumer Health Apps for Apple’s iPhone.� GH BP 2012/01. London. http://www.chathamhouse.org/ http://mobihealthnews.com/13368/report-13k-iphone- sites/default/files/public/Research/Global%20Health/0112bp consumer-health-apps-in-2012/. _chand.pdf. Patil, D. A. 2011. “Mobile for Health (mHealth) in Developing Changamka. 2012. http://www.changamka.co.ke/html/welcome Countries: Application of 4 Ps of Social Marketing.� Journal of .html. Health Informatics in Developing Countries 5 (2): 317–26. Freng, I., S. Sherrington, D. Dicks, N. Gray, and T. Chang. 2011. Qiang, C. Z., M. Yamamichi, V. Hausman, R. Miller, and D. “Mobile Communications for Medical Care.� http://www.csap Altman. 2012. “Mobile Applications for the Health Sector.� ICT .cam.ac.uk/media/uploads/files/1/mobile-communications- Sector Unit, World Bank, Washington, DC. http://sitere- for-medical-care.pdf. sources.worldbank.org/INFORMATIONANDCOMMUNI- Gombachika, H., and M. Monawe. 2011. “Correlation Analysis of CATIONANDTECHNOLOGIES/Resources/mHealth_report_ Attitudes towards SMS Technology and Blood Donation (Apr_2012).pdf. 58 Information and Communications for Development 2012 Perera, I. 2009. “Implementing Healthcare Information in Rural Developing World.� Washington, DC, and Berkshire, UK: UN Communities in Sri Lanka: A Novel Approach with Mobile Foundation-Vodafone Foundation Partnership. http://www Communication.� Journal of Health Informatics in Developing .vitalwaveconsulting.com/pdf/mHealth.pdf. Countries 3 (2): 24–29. http://www.jhidc.org/index.php/jhidc ———. 2011. “eTransform Africa Sector Report: Health Sector /issue/view/8. Study.� http://www.etransformafrica.org/sites/default/files/ RapidSMS. 2012. “The Jokko Initiative.� http://www.rapidsms.org/ Complete-Report-and-Summary-Health.pdf. case-studies/senegal-the-jokko-initiative. WawaRed. 2012. http://wawared.lamula.pe/. Telecoms Tech. 2012. “US$1.3 billion: The Market for mHealth Wooton, R., N. G. Patil, R. E. Scott, and K. Ho, eds. 2009. Telehealth Applications in 2012.� http://www.telecomstechnews.com/ in the Developing World. Royal Society of Medicine Press/ blog-hub/2012/jan/30/us-13-billion-the-market-for-mhealth- IDRC. applications-in-2012/. WHO (World Health Organization). 2005. “Global eHealth Strat- Telenor Group. 2012. “New Study: The World Is Ready for Mobile egy.� World Health Assembly Resolution 58.58, Geneva. http:// Healthcare.� Press release. http://telenor.com/news-and- a p p s . w h o. i n t / g b / e bw h a / p d f _ f i l e s / W H A 5 8 / W H A 5 8 media/press-releases/2012/new-study-the-world-is-ready-for- _28-en.pdf. mobile-healthcare/. ———. 2011. “mHealth: New Horizons for Health through Mobile Vital Wave Consulting. 2009. “mHealth for Development: The Technologies: Second Global Survey on eHealth.� http://whqlibdoc Opportunity of Mobile Technology for Healthcare in the .who.int/publications/2011/9789241564250_eng.pdf. mHealth 59 Chapter 4 Mobile Money for Financial Inclusion Kevin Donovan obile financial services are among the most payments (such as peer-to-peer transfers), finance (such as M promising mobile applications in the devel- oping world. Mobile money could become a general platform that transforms entire economies, as it is insurance products), and banking (such as account balance inquiries). In practice, a variety of means can be used such as sending text messages to transfer value or accessing bank adopted across commerce, health care, agriculture, and account details via the mobile internet (figure 4.1). Special other sectors. To date, at least 110 money mobile systems “contactless� technologies are available that allow phones to have been deployed, with more than 40 million users. The transfer money to contactless cash registers. most well-known system, M-PESA, started in Kenya and is Although mobile phones are central to all these uses, now operational in six countries; it has 20 million users who mobile money is more than just technology—it needs a transferred $500 million a month during 2011.1 While the cash-in, cash-out infrastructure, usually accomplished benefits of mobile money payment systems are clear, through a network of “cash merchants� (or “agents�), who observers remain divided over whether mobile money receive a small commission for turning cash into electronic systems are truly fulfilling their growth potential. value (and vice versa). This chapter evaluates the benefits and potential impact of Because the mobile money industry exists at the inter- mobile money, especially for promoting financial inclusion section of finance and telecommunications, it has a diverse in the developing world, before providing an overview of the set of stakeholders, with players from different fields in key factors driving the growth of mobile money services. It competition. Mobile network operators, banks, and increas- also considers some of the barriers and obstacles hindering ingly new entrants, such as payment card firms, continue to their deployment. Finally, it identifies emerging issues that catalyze the industry with innovative offerings, but to be the industry will face over the coming years. sustainable, these must be met with sufficient demand from consumers and firms—a variable missing in many contexts. A host of supporting businesses, such as agents and liquid- Mobile money: an ecosystem ity management firms, are also necessary. In areas where it approach has proved successful, mobile money has created a platform At the most basic level, mobile money is the provision of for start-ups to build upon (Kendall et al. 2011). Finally, all financial services through a mobile device (box 4.1).2 This of this must happen in an environment with appropriate broad definition encompasses a range of services, including government regulations for both finance and the ICT 61 Box 4.1 One device, many channels Mobile phones are multifunctional devices that allow for a variety of communication methods. These range from ubiquitous voice and SMS channels to more sophisticated means such as soft- ware applications or web browsers. To be a viable solution for mobile money, the channel should ideally be universally available (including the cheapest mobile phones) and must be secure. In practice, this requirement largely limits mobile money to using a standard network service, such as USSD (Unstructured Supplementary Service Data) or SMS (short message system), or an application preloaded on a unique SIM card. Since mobile operators control both of these chan- nels, they remain essential gatekeepers in deploying mobile money. Sources: http://mmublog.org/blog/on-channels/; http://www.ictinagriculture.org/ictinag/sites/ictinagriculture.org/files/ web_Module3.pdf. Figure 4.1 Different types of mobile financial services poor can slow economic growth and exacerbate inequality (Demirgüç-Kunt, Beck, and Honahan 2008). Mobile finance Mobile banking Finding innovative models to extend financial services to including including the poor has now become an urgent challenge. The excite- Credit | Insurance | Savings Transactional | Informational ment around mobile money has arisen in part because it is Mobile payments widely seen as an effective way to provide access to finance to including Person-to-person | Government-to-person | Business-to-business millions of people around the globe. According to the Consultative Group to Assist the Poor (CGAP), roughly Source: Adapted from Gencer 2011. 1 billion people have a mobile phone but no bank account. Providing them access to mobile financial services will involve sector, as well as appropriate safeguards for consumer difficult implementation that is unlikely to succeed quickly. protection. In addition to extending financial services to the poor, mobile money is expected to improve productivity by increasing the efficiency and lowering the cost of transac- The financial inclusion imperative tions, improving security, generating new employment Poverty is more than just a lack of money. It involves a lack opportunities, and creating a platform on which other busi- of access to the instruments and means through which the nesses can grow. poor could improve their lives. Exclusion from the formal Mobile money could transform financial inclusion. financial system has increasingly been identified as one of “Where most financial inclusion models have employed the barriers to a world without poverty. In many develop- either ‘credit-led’ or ‘savings-led’ approaches, the M-PESA ing countries, more than half of households lack an experience suggests that there may be a third approach— account with a financial institution, while small firms focusing on building the payment ‘rails’ on which a broader frequently cite difficulty in accessing and affording financ- set of financial services can ride,� wrote the authors of one ing as a key constraint on their growth. This exclusion report (Mas and Radcliffe 2010). As illustrated in the next does not necessarily mean that the poor lack active finan- section, while benefits from the simple diffusion of an cial lives: in fact, the fragility of their situation has led to improved infrastructural “rail� are significant, even greater the development of sophisticated informal financial impact arises because mobile money systems can serve as a instruments. However, the use of only informal instru- platform for additional innovations, whether they be bill ments means that the poor are limited in their ability to payment services that avoid lengthy queue times or more save, repay debts, and manage risk responsibly. On a striking examples such as efficient conditional cash transfers macroeconomic level, these financial constraints on the for drought relief or compensation.3 In places where no 62 Information and Communications for Development 2012 financial infrastructure exists, this type of change is truly Inherent benefits transformational. Mobile money is often successful because it is considerably cheaper than other alternatives to cash. In an international comparison of 26 banks, McKay and Pickens (2010) found What is the impact of mobile money? that branchless banking (including mobile money) was 19 According to data from the GSM Association, most of the percent cheaper on average than alternative services. At low 100-plus deployments of mobile money systems have been transaction amounts or for informal money transfer in developing countries, with around half in Africa alone options, this difference more than doubled.5 In Kenya (figure 4.2). Mobile money systems can be made available M-PESA was routinely one-third to one-half as expensive as wherever there is wireless phone service, helping to over- alternative systems. Lower costs directly translate into come distance, as well as the lack of branch offices in rural money the poor can keep—in Kenya the amount of money areas (box 4.2). remitted increased when transferred using M-PESA Since mobile money is often linked to financial inclusion, compared with traditional forms of remittances. Conversely, it is vital to understand how and under what conditions where transaction costs are high, as in Botswana where the mobile money applications can extend financial services to cost per transaction is a minimum of 8 pula ($1.07), mobile the poor. Support for mobile money initiatives from govern- money has been slow to take root. ments, nongovernmental organizations, and the interna- Well-supervised mobile money can be safer than alterna- tional development community needs to be justified by tives, including cash. Early studies of M-PESA in low- assessing the impact on development goals such as financial income areas found that the risk of muggings declined, inclusion, poverty reduction, increased productivity, and because cash was less evident. Because it is less visible than risk management. cash, mobile money also has consequences for privacy and Although the mobile money industry has achieved signif- autonomy. Research has found that women are able to have icant scale in only a handful of countries, a growing number personal savings without seeking permission from their of studies are establishing its impact in a variety of areas. Its husbands (Morawczynski 2009), but, of course, this auton- potential advantages include benefits arising from the inher- omy holds true for both genders.6 ent characteristics of the services; benefits arising organically The speed and liquidity of mobile money are also key from widespread usage and network effects; and benefits benefits. The limited assets the poor own often take the form arising from purposeful and innovative applications, either of valuable objects (such as livestock or gold), which are made by developers or created by people’s uses of mobile relatively illiquid. In times of crisis, such assets can be diffi- money services.4 cult to realize quickly, and their value may decline if the Figure 4.2 Global mobile money deployments a. Number of countries with at least one mobile b. Number of mobile money deployments money deployment by World Bank region, March 2012 80 74 60 53 50 60 40 Number Number 40 31 30 56 21 20 20 9 13 2 2 3 4 6 10 3 5 16 20 11 13 0 0 a sia n sia a ed ic ric ea c cif 01 02 03 04 05 08 09 10 11 06 07 fri lop hA lA Af ibb Pa A 20 20 20 20 20 20 20 20 20 20 20 tra ve ut rth an ar & De So en C r No sia ha he dC Sa tA d dt an an b- s an Ea Su st pe ica Ea ro Eu er le Am idd M tin La Source: GSMA Mobile Money Tracker 2012. Mobile Money for Financial Inclusion 63 Box 4.2 Using mobile money Mobile money applications are typically small pieces of software embedded on a SIM card or available over a mobile network. A customer can use an inexpensive mobile to send value to someone else. To change this digital value into cash, a user simply visits a retail agent who verifies the user’s identity and makes the switch. In this way, money can cross enormous distances at the speed of a text message. Consider a young Tanzanian who has moved to Dar es Salaam to find work. With mobile money, he can send regular, small payments to his family at their rural home without needing to pay and trust a courier or take it himself. His family can then exchange the digital value for cash at a local agent. market floods with other families seeking to convert similar money allows many to get cash when and where they need it assets to cash at the same time. Moreover, sending gold (Stuart and Cohen 2011). bracelets or cash to a family or friend in need can be a risky Mobile money can also prove commercially significant enterprise. Mobile money can be an accessible and conven- for service providers, when it reaches scale. Although the ient medium for the delivery of financial services and more transaction fees that mobile money providers charge are reliable than traditional, informal methods. individually quite small, in total, they can represent an important revenue source. For example, Safaricom, the Benefits from scale mobile operator that offers M-PESA, reported mobile In some jurisdictions, mobile money has achieved critical money revenues for the first half of 2011 of K Sh 7.9 billion mass, so nonusers are encouraged to adopt the systems used ($90 million). In addition, cash agents may also gain by their peers. When the poor are connected on a large scale, commercial benefit from the fees they receive. they are able to use mobile money to improve their liveli- hoods. The best data available on this point comes again Benefits from innovation from Kenya, where households with access to mobile money Improving the ability of the poor to transfer money is were better able than those without to manage negative certainly beneficial, but in isolation, mobile transfer ser - shocks (including job loss, death of livestock, or problems vices do not capture the full potential of mobile money to with harvests). Whereas households that did not use M- enhance financial inclusion. Early studies of South PESA saw consumption fall by 6–10 percent on average, M- African mobile money found that while it had the poten- PESA users were often able to fully absorb the shocks, tial to advance financial inclusion, it had not increased because they received more remittances and lost less to access to banking, especially compared with nontechno- transaction costs (Suri and Jack 2011). Evidence of such logical efforts, such as a particular type of bank account “livelihood strategies� was also evident during the violence designed especially for the poor (Porteous 2007). In following Kenya’s 2007 election, during which M-PESA Kenya, for example, the predominant use of M-PESA “became one of the only means through which [residents of is still sending money, although some people use it for Nairobi’s informal Kibera settlement] could access cash� savings (Stuart and Cohen 2011). Access and use of more (Morawczynski 2009). Even in less tumultuous times, sophisticated financial services such as savings, credit, and mobile money at scale can serve to meet the needs of the insurance could prove far more beneficial to the poor. To poor: research in Kenya found that M-PESA was a useful develop these services, businesses, governments, and means to access cash. Often the poor lack fungible sources of other institutions must innovate actively on top of the exchange such as cash, and through the network of cash payment services that are being deployed by mobile agents and people’s contacts willing to send value, mobile money operators.7 64 Information and Communications for Development 2012 Some organizations are deliberately using mobile money Developing the necessary cross-sectoral partnerships— to enhance their traditional offerings. For example, during a including bridging cultures and regulations—may therefore recent drought in Niger, a set of randomly selected house- prove difficult. holds received cash transfers via mobile money (Aker et al. Additionally, mobile money services represent a two- 2011). In comparison with physical cash, this trial found sided market, and new deployments must convince both lower variable costs for senders, as well as lower costs for agents (supply) and customers (demand) to sign up for the recipients. Over the course of the crisis, recipient households service in sufficient quantity to be viable. Building and prop- also enjoyed better diets and depleted fewer assets. erly incentivizing the agent network is no small task, and Insurance, credit, and savings services are now being maintaining the necessary cash liquidity at the outlets can developed atop mature mobile money systems. Kilimo prove a constant challenge. Winning and retaining the trust Salama is a micro-insurance product that uses M-PESA to of customers, including those who are poor and new to the provide payouts to smallholder farmers whose crops fail. In technology, is central to success. Commercial viability in this its second year of operation, 12,000 farmers were insured, industry requires scale, and operators are faced with the and 10 percent of those received payouts of up to 50 percent trade-off between higher costs to recoup their investments of their insured inputs (Sen and Choudhary 2011). Likewise, or lower costs to reach scale and build a mass market (Mas Equity Bank and Safaricom have partnered to offer and Radcliffe 2010). M-Kesho, a mobile service that offers microsavings Despite these challenges, mobile money has grown in a accounts, credit, and insurance. As individuals develop variety of markets. Although the International Finance financial histories with mobile money, the ability to provide Corporation (IFC) identified more than 50 factors influenc- credit can expand because financial institutions will be able ing the growth of mobile money, 3 are especially important to analyze those histories and assign credit scores. (IFC 2011): regulation, competition with other instruments The impact of mobile money is also likely to extend to the of financial access, and user perceptions and skills. public sector through increased efficiency and reach. Government adoption of mobile money is still in its infancy, Regulation but a study by McKinsey for the Gates Foundation estimates Since mobile money straddles finance and telecommunica- that connecting poor Indian households to an electronic tions, it faces regulation originating within two different payment system for cash transfers would have considerable sectors. For mobile money to develop, regulations must impact through reduced leakages, transaction costs, and encourage inclusiveness, while minimizing fraud and risk. overheads (Lochan et al. 2010). It would also improve the The uncertainty associated with innovative industries means government’s ability to monitor financial flows, collect tax that regulations must be incremental and proportional. revenues, and reduce illicit activity. Government use of Kenya’s initial success with mobile money was arguably mobile money—such as salary disbursements—could prove based on a virtual absence of formal regulation in favor of to be an enormous driver of the service throughout the industry-government engagement (World Bank 2010). economy on the whole. However, since mobile money services manage the limited capital of the poor, caution is essential (USAID 2010). Successful regulation is usually marked by collaborative Growing mobile money: challenges exchange between industry, government, and civil society. and success stories For example, regulation should allow agents outside of bank Despite a growing number of successes, the mobile money branches to handle financial transactions and develop tiered industry faces a number of challenges. Mobile money anti-money-laundering and know-your-customer (AML/ deployments in developing countries often target customers KYC) requirements. To facilitate more sophisticated ser- who may be poor, dispersed, and remote. Mobile money also vice offerings, ongoing regulatory development will be spans two distinct industries with different business models. necessary—for example, most mobile money is regulated Telecommunications and payments are transaction-based, as “payments,� “denying e-money accounts the benefit of with fees collected on transactions; conversely, banking is interest payments and deposit insurance� (Ehrbeck and float-based, with money earned through holding deposits. Tarazi 2011). In considering these new regulatory issues, Mobile Money for Financial Inclusion 65 protection against fraud and failure, including regular money feasible. As mobile telephony continues to evolve monitoring by financial regulators, is essential. But it is toward more sophisticated devices and services, the range of also important to remember the goal is to find ways to feasible mobile money applications will continue to expand.9 provide society’s poor with financial services, and often Over the coming years, three technological developments will mobile is the most promising way.8 have a significant impact on mobile money: the rise of smart- phones, near field communications, and biometrics. Existing status of finance and mobile industries Mobile money is by no means the only instrument for extend- Smartphones. Over the coming years, smartphones will ing access to finance to the poor; cooperatives, savings and become more widespread in developing markets. The rela- loans groups, and even ATMs (automated teller machines) are tively well-off and young individuals who will adopt them popular throughout the developing world. Among the factors first will serve as important trendsetters, but adoption will that will determine whether mobile money will succeed is the eventually become more widespread. Already, in Kenya, extent to which alternative options are accessible and desir- Huawei is offering an Android-powered smartphone for able. In places with sophisticated financial or mobile indus- under $100, and when smartphones begin to be sold on the tries, the commitment of leading firms to mobile money can second- and third-hand market, they will be even more do much to drive adoption of the service, but already-existing widely accessible. The enhanced capabilities of smartphones alternatives or a limited market size can limit the economies will mean that mobile money applications will move beyond of scale necessary for mobile money to succeed. On the other channels closely controlled by the mobile operators to plat- hand, too low a volume of existing financial services can be a forms that are more open to competition (although SMS detriment for mobile money because cash agents need a way and USSD functionality will remain important for reaching to manage their liquidity (such as traveling to bank branches, a broader base of customers). Because smartphones serve as for example). In short, mobile money is one part of the solu- a gateway to the internet, a broader range of applications will tion that also requires other forms of infrastructure and become available, enhancing the need for interoperability. resources (box 4. 3). These changes will be accompanied by opportunities, such as the chance to use graphical interfaces with illiterate popu- User perceptions, behavior, and skills lations, and challenges, such as the growth in data traffic and The success of mobile money also rests on various factors increased burden on network capacities. Smartphones will relating to end users. There may be considerable distrust of also drive home the importance of device-makers to mobile the formal financial services, or people may be uneasy about money. parting with their cash. Mobile money operations need to create a clear and trustworthy value proposition that fits Near field communications. Near field communications within social and cultural practices. For example, mobile (NFC) is a technology that allows devices to communicate phones are widely available, but they are not universal, and through mere proximity, usually by waving a specially many people in the developing world share or rent phones. equipped phone or card near a receiving device, as opposed Designing mobile money requires a careful understanding to having to physically swipe it. NFC could serve to make of these diverse interactions. transactions more efficient and secure by reducing errors, such as those that arise from mistyped numbers. In the Emerging issues in mobile money coming years, more phones will be equipped with NFC, Mobile money is a fast-moving and wide-ranging industry, which is expected to become more popular for financial but as it matures and evolves, several emerging issues are transactions. For mobile money, this means that transactions worth increased attention. This section flags these issues as a can be completed by waving a phone near a receiver, as first step toward finding longer-term solutions. opposed to having to text value to a recipient. Since NFC requires a new infrastructure to receive the payments, it may Technological issues be slow to grow, but as wallets become digitized onto phones, It was technological change—in the form of less expensive mobile money agents and businesses may start to use their phones and expanded network coverage—that made mobile own NFC-enabled smartphones to receive payments. Already 66 Information and Communications for Development 2012 Box 4.3 Business models for mobile money Although it has received both direct and indirect support from the public sector, to date, mobile money remains a private sector enterprise. To achieve profitability, mobile money providers have pioneered three general business models: mobile-operator-led, bank-led, and collabora- tive. Because operators control the mobile platform and have significant distribution capacity through their existing retail agent networks, it is logical that mobile money deployments will often be initiated by operators who may partner or collaborate with a bank. In some places, such as Pakistan, where the operator Telenor purchased a 51 percent stake in Tameer Micro- finance Bank, the boundaries between the two entities may be blurred. A variety of business models exist for mobile money. Although M-PESA popularized a model based primarily on peer-to-peer transfers, mobile money systems elsewhere are quite different. For example, in South Africa, WIZZIT is an independent mobile money provider that works over all mobile networks and that has partnered with banks to provide customers with easily accessible accounts. In Thailand, the two relatively successful mobile money operations have partnered with retailers from the start and emphasize bill payment offerings. According to the International Finance Corporation’s Mobile Money Study, in a given market, the business case for mobile money will be driven by those players with the strongest incentive to develop mobile money; the primary value proposition for targeted customers; and the regulation, demand, and partnership requirements. Combining these variables, the Inter- national Finance Corporation has developed mobile money demand curves that show how mobile money has different appeal in different environments. Box figure 4.3.1 Mobile money demand curves high Relative demand for low-cos, low-speed, Relative demand for high-speed, Japan high-volume transactions infrequent transactions Nigeria Kenya United States Brazil Sri Lanka Thailand Developing economies Developed economies low low Level of infrastructure high development ALTERNATIVE INFRASTRUCTURE TRANSITION PHASE COLLABORATION PLAYERS Mobile network Banks Multiple partners operators (continued next page) Mobile Money for Financial Inclusion 67 Box 4.3 (continued) The black curve represents mobile money demand for developing economies. As develop- ing countries progress, financial infrastructure develops, and competition from banks, credit card companies, and other financial institutions increases. The black curve becomes dotted because demand changes from low-cost, low-speed, and infrequent to high-speed and high- volume as represented by the blue curve. The green curve starts off dotted because devel- oped countries already have substantial financial infrastructure, thus demand for low-cost, low-speed, infrequent transactions is low. The continuum is divided into three parts: alterna- tive infrastructure, transition phase, and collaboration. In developing economies mobile money acts as an alternative infrastructure to existing financial services; during the transition phase mobile money moves from an alternative infrastructure to a complementary one. In the collab- oration phase mobile money must fully integrate with the financial infrastructure. Source: IFC 2011. at the start of 2012, Absa, a large South African bank, was development is important because increased competition, testing NFC deployments for its payments. not to mention the possibility of digital money lessening the need for cash, could reduce agents’ profits: in Kenya, Biometrics. The Center for Global Development estimates M-PESA agents have already seen daily profits drop from $5 that over 450 million people in developing countries have had to $4 (Pickens 2011). their biometric data recorded, and this number is expected to As mobile money providers have realized the importance triple over the next five years (Gelb and Decker 2011). The of agents in their business models, four interlinked problems most ambitious biometric program—India’s Project Aadhaar, have emerged: profitability, proximity, liquidity, and trust which is aiming to provide a universal ID system for all citi- (Maurer, Nelms, and Rea forthcoming). The agent model is zens, including iris scans, ten fingerprints, and a picture of founded on the exchange of cash through a franchise model, each face—has been explicitly linked to financial inclusion.10 so the profitability of agents is vital for success. If the agent These identification schemes are typically associated with network grows too quickly and saturates the market, security initiatives, but they are also seen as a means of however, mobile money agents may not have sufficient improving delivery of cash by governments and development transactions to remain in business. If agents’ costs for agencies. Many of these programs are in the early stages, and managing their cash liquidity are too high, they will also significant challenges abound. Deploying biometric systems suffer. Finally, if the agents behave improperly or fail to can be very expensive, and ensuring high accuracy is often out develop relationships with their customers, the all-impor- of reach. Further, it is likely to raise political concerns given tant client trust will not develop. the implications for citizen privacy, so some countries are opting for less intrusive means of identification. Internationalization of mobile money International remittances are one of the largest sources of The changing role of agent networks external financing in developing countries and often serve as Understanding the human dynamics of a growth market is a lifeline to the poor.11 However, the costs of transmitting essential. Building and incentivizing networks that serve as money from abroad are often large and uncertain. For exam- the cash-in, cash-out point of contact, as well as customers’ ple, according to World Bank data, the cost of sending money primary interface with the brand, is difficult and costly. across the Tanzania-Kenya border was nearly 10 times the Many operators have found that existing airtime resellers are price of sending money from the United Kingdom to Pakistan useful agents, but other intermediaries (such as large-scale in 2011 (figure 4.3). Easing and improving international retail chains or post offices) are also likely candidates. This remittances will have significant development impacts, just 68 Information and Communications for Development 2012 Figure 4.3 The most and least expensive remittance money industry. In cases where a mobile money service is corridors tied to a dominant mobile network operator (as in the case of Kenya’s Safaricom, which has 68 percent of the mobile 60 50 49.19 49.19 47.20 subscribers market; see Communications Commission of 44.66 40 36.11 Kenya 2011), that operator is at an advantage in dictating US dollars 30 the terms of the product. 20 The appropriate form of regulation is still emerging and 10 4.40 5.15 5.99 6.33 6.40 will depend on context. Premature competition regulation 0 may even stymie the growth of mobile money. As a recent da da a bia ue sh an es an es ny pin pin de an an biq ist is t m Ke gla Rw k ak Ug Za ilip ilip am Pa ia– World Economic Forum report noted, “initial adoption –P a– ia– an ia– Ph Ph s– oz an UK ric B s– M e– te an an e– nz Af ra a– te or nz nz Ta or appears to be driven by constrained access to formal finan- mi ra ap uth ric Ta Ta ap mi bE ng Af So ng bE Si ra uth Si dA cial services, as opposed to well-developed institutions and ra So dA ite ite Un competitive markets�(WEF 2011). On the other hand, wait- Un ing too long to curtail anticompetitive practices may incur Source: World Bank (http://remittanceprices.worldbank.org). Note: Data is for Q3 2011. social and financial costs to society. One of the main ways to reduce mobile money market domination is through interoperability (box 4.4). Interoper- ability can occur at various levels: in Nigeria, where the as easing remittance transactions at the domestic level has Central Bank has been keen to avoid a dominant market done (Maimbo, Saranga, and Strychacz 2011). Prices are player, interoperability is required at the level of the bank, the high because of underdeveloped payment systems infra- switch, and the payment channel (IFC 2011). In other coun- structure, inappropriate legal frameworks, and the difficulty tries, mobile money occurs in a “walled garden� because many migrants have obtaining identification in order to interoperability is not technically allowed. Consumers wish- access finance; a lack of transparency, competition, and ing to swap between mobile money services must have multi- consumer protection has also kept prices high. Mobile ple SIM cards and use cash to exchange between different money could do much to ease this situation, but regulatory digital wallets (incurring time, effort, and extra fees). assistance and the creation of the appropriate payment Sensing a market opportunity, third-party firms are systems infrastructure will be required. beginning to offer interoperability between different mobile Policy-makers are justifiably concerned about criminal money services. Because these interoperability systems are and terrorist financing, as well as the monetary policy issues often unofficial, however, they remain tenuous. While some arising from illegal cross-border remittance flows, but regula- observers are of the opinion that consumer demand will tors need to give increased attention to easing the policy ultimately pressure providers to allow interoperability in constraints on internationalization of mobile money. Because time (IFC 2011), others detect a potential market failure. multinational negotiations are time-consuming, smaller pilot Mobile money operators are often reluctant to allow projects could be implemented to explore how to improve the formal interoperability because, after investing heavily in regulation of international mobile money remittances. their product, they do not want to make it easy for Regions with currency unions, such as parts of West Africa, or customers to move their money to competitors. In fact, in where existing infrastructure is present, such as between markets where customers frequently change mobile opera- Mexico and the United States, may lead the way here because tors to save money, mobile money services are seen as a key foreign exchange considerations have been eliminated. way of keeping customers locked into an operator’s own network. However, it has been argued that interoperability Competition and interoperability will benefit operators by expanding the pool of customers, Additional regulatory attention is also needed for issues of reducing incentives to have multiple SIM cards (and thus to competition and interoperability. Like other network make calls on competing networks), and minimizing the industries, economies of scale and high barriers to entry need for retail agents to have cash, which is costly to move could create uncompetitive market outcomes in the mobile around between different agents (Mas 2011). Interoperability Mobile Money for Financial Inclusion 69 Box 4.4 Interoperability and innovation in mobile money The excitement surrounding successful mobile money deployments has spurred significant additional innovative activity. Surveying the landscape in Kenya, Kendall et al. (2011) found that M-PESA has emerged as a platform for a wide variety of new applications and services. Busi- nesses have started integrating M-PESA into their activities, often to improve efficiencies and reduce costs. Other entrepreneurial ventures offer entirely new services based on the mobile phone, such as a medical savings plan from Changamka Microhealth Ltd. Finally, an entirely new category of businesses is developing; these businesses serve as intermediary bridge- builders, allowing others to integrate with mobile money. For example, Kopo Kopo is a start- up that offers smaller financial institutions and competing mobile money providers the technical means to integrate with M-PESA. There is reason to worry that this initial flourishing is tenuous. The lack of seamless inter- operability (for example, through an M-PESA application programming interface) is a common complaint, raising the costs of working with M-PESA. Because it is a proprietary service of Vodafone, the businesses building on top of the platform are highly dependent upon the choices of Vodafone and its local affiliate, Safaricom. Source: http://www.microsave.org/research_paper/analysis-of-financial-institutions-riding-the-m-pesa-rails. may also benefit mobile money agents who currently have to mentioned, interoperability could serve as a primary lever by maintain redundant infrastructure for each mobile money which to reduce redundant costs and expand access. deployment they wish to serve, as well as enhancing overall Finally, many would-be mobile money users lack the efficiency gains in the economy. But because premature necessary skills—including basic and quantitative literacy— interoperability may limit the market’s development, regula- that are necessary to fully realize the benefit of mobile tors must approach this issue with caution. money. Mobile money providers have an incentive to educate consumers about their products, and governments Universal access and service can support this through promoting transparent business The populations least likely to feel the benefits of mobile practices. money are societies’ poorest citizens because they have the least connectivity, ability to pay, and requisite skills. Product innovation for meaningful Both mobile network operators and financial institu- financial inclusion tions find it commercially infeasible to operate in remote Today, concerns about excluding the poorest from mobile rural areas. In the realm of telecommunications, this money are premature in most developing countries. Despite market failure has led to universal access and service funds the runaway success of a few deployments, in the vast major- that aim to connect all citizens, and the rationale for ity of cases, mobile money services have struggled to achieve extending those to programs to mobile financial services the scale at which they might raise distributional concerns.12 should be considered. Surveying the globe, CGAP found that only one in four Because mobile money has been driven by for-profit enti- branchless banking services (a broad category that includes ties, most transactions incur a fee that many poor find diffi- mobile money) had more than 1 million registered cult to pay, even if they are willing to do so because of the customers, and of those launched since 2007, only 1 in 15 convenience and speed of transfer. Regulators must ensure has more than 250,000 active customers (Fathallah, Mino, that the mobile money industry is competitive to allow well- and Pickens 2011). Furthermore, customer use of many functioning market forces to drive prices down. As mobile money services remains low—often only a couple of 70 Information and Communications for Development 2012 transactions a month. In many cases, the transaction fees money, leading to family troubles arising from worries about remain too high to enable mobile money to replace cash for their whereabouts, potential infidelity, and financial stress. petty purchases. Another example might be the use of mobile money in At the moment, however, a “product gap� exists in most microfinance. Many microfinance supporters believe that countries between the financial services the poor are being the social pressures exerted through face-to-face group offered and the services they want (Morawczynski and meetings are essential for generating the high rates of repay- Krepp 2011). The model so successfully pioneered by ment that make microfinance viable. If they are correct, the M-PESA—starting with peer-to-peer transfers—has been disintermediation created by mobile money could prove widely replicated but may not fit well in other contexts. For harmful to microfinance. The Gates Foundation argues that example, an extensive ATM network already meets many of bringing together different models such as banks, co-ops, the consumer financial needs in Thailand. By definition, savings-led groups, and mobile money could leverage their mobile money will not have a comparative advantage in respective strengths, instead of “creating a single synthetic every location or for every service, so the business environ- model� (WEF 2011). ment must be enabling and open to allow businesses to Finally, as mobile money matures, people are increasingly pioneer new forms of mobile money tailored to local discussing the “cashless society.� Although that is unlikely, circumstances. mobile money may displace many uses of cash. Already, the Product innovation is also essential to realize the full Central Bank of Nigeria is promoting “cashless Lagos� in an potential of mobile money. Currently, only 1 in 8 branchless effort to reduce the amount of cash circulating in the econ- banking deployments offer functionality beyond basic peer- omy in favor of electronic transactions, including direct to-peer transfers and e-wallet services. Indeed, the IFC’s credit and debit, payment cards, internet-based services, and study of mobile money in Brazil, Nigeria, Sri Lanka, and mobile money. The U.S. Agency for International Develop- Thailand found that the most popular uses for mobile money ment, too, is arguing for adopting alternatives that are were essentially moving money over distance. However, “better than cash� (USAID 2010). If this trend toward customers also want the ability to move money over time (in replacing cash continues, financial transactions could the form of savings, insurance, and credit). As argued above, become uniquely identified and recorded, introducing simply formalizing people’s finances onto the mobile plat- complexities for consumer privacy. Others have suggested form falls short of meaningful financial inclusion—for that, that the provision of money by private companies over the simple “additive� models of mobile money (where mobile private infrastructure risks undermining an important func- is just another channel) is to move to “transformational� tion of the public sector, namely, that the means of value mobile money (where finance is extended to those previously transfer are not “owned� by anyone. unbanked, excluded populations) (Porteous 2007). While a mobile payment infrastructure is a first step, tailored prod- Conclusions ucts and services that enable the poor to better manage and capitalize on their assets must follow. Many of the characteristics that make mobile money so promising—its scale and impact, its varied uses, and the Mitigating the growing pains novelty of its role—are also reasons why achieving these In celebrating mobile money as a disruptive innovation, it is hopes is so difficult. While exciting, the success of a few important to remember the second half of that phrase. The mobile money deployments should not shelter the fact that introduction of technology into communities can upset those examples remain the exception, not the rule. With this existing practices, sometimes causing stress or worse. caution in mind, governments, donors, and industry have Although humans are adaptive and generally adopt mobile good reason to support the creation of vibrant mobile money willingly, it is worth being on guard for undesirable money services that include the world’s poor in financial disruptions from innovation. For example, ethnographic markets and allow them to manage and use their own work from Kenya suggests that mobile money users in money. Although far from the only mechanism, mobile is Nairobi who had previously traveled frequently to family in certainly one of the most powerful means by which to real- rural areas did so less often after they began to use mobile ize this promise. Mobile Money for Financial Inclusion 71 Notes with 64 million people in the surveyed countries not using any formal remittance instrument. 1. Vodafone Annual Report 2011 (http://www.vodafone.com/ 12. Of course, this is not to say that these subscale examples will content/annualreport/annual_report11/business-review/strategy- not, in the future, raise those concerns. Indeed the very in-action/focus-on-key-areas-of-growth-potential/emerging- purpose of this section is to consider that possibility. markets.html). 2. Mobile money can be considered a subsector of a wider industry—branchless banking that uses a variety of methods References and technology to extend financial access. 3. An example of the latter is the World Bank–funded initiative Aker, Jenny, Rachid Boumnijel, Amanda McClelland, and Niall to use mobile phones to compensate ex-combatants in the Tierney. 2011. “Zap It to Me: The Short-Term Impacts of a Democratic Republic of Congo; see http://www.mdrp.org/ Mobile Cash Transfer Program.� Working paper 268, Center PDFs/In_Focus_3.pdf. for Global Development, Washington, DC. 4. For additional information on the adoption and impact of Chatain, Pierre-Laurent, Andrew Zerzan, Wameek Noor, Najah mobile money, see Institute for Money, Technology and Dannaoui, and Louis de Koker. 2011. Protecting Mobile Money Financial Inclusion (http://www.imtfi.uci.edu) and the Finan- against Financial Crimes: Global Policy Challenges and Solu- cial Services Assessment project (http://www.fsassessment tions. Washington, DC: World Bank. .umd.edu/). Communications Commission of Kenya. 2011. “Quarterly Sector 5. In reality, the savings are likely even greater for mobile money Statistics Report: Q3 2011.� Nairobi. because this study grouped mobile money with other meth- Demirgüç-Kunt, Asli, Thorsten Beck, and Patrick Honohan. 2008. ods of branchless banking and did not account for the savings Finance for All?: Policies and Pitfalls in Expanding Access. arising from the reduced travel. Washington, DC: World Bank. 6. At the same time, anecdotal evidence suggests that the need to Ehrbeck, Tilman, and Michael Tarazi. 2011. “Putting the Banking go to an agent to cash in or cash out can advertise a person’s in Branchless Banking: The Case for Interest-Bearing and relative wealth, perhaps increasing risk. Insured E-Money Savings Accounts.� The Mobile Financial 7. Despite the justifiable promise of such approaches, a word Services Development Report, 37–42. Washington, DC: World of caution is worthwhile. Innovation implies the possibility Economic Forum. of failure, and given the precarious situations of the poor, Fathallah, Sarah, Toru Mino, and Mark Pickens. 2011. “The Case entities wishing to improve the poor’s financial situation for More Product Innovation in Mobile Money and Branchless through mobile money must take every caution to under- Banking.� Consultative Group to Assist the Poor, Web log post. stand the risk involved; see, for example, USAID 2010. As is October 14. http://technology.cgap.org/2011/10/14/the-case- evident with other industries working with the poor, for-more-product-innovation-in-mobile-money-and-branch- changing incentives and policies can result in disaster. less-banking/. Furthermore, creating dependencies on private infrastruc- ture can be disastrous in the event of bankruptcy or other Gelb, Alan, and Caroline Decker. 2011. “Cash at Your Fingertips: disruptions. Biometric Technology for Transfers in Developing and Resource-Rich Countries.� Working paper 253, Center for 8. For additional information, see the regulatory resources from Global Development, Washington, DC. the Consultative Group to Assist the Poor and Chatain et al. (2011). Gencer, Menekse. 2011. “The Mobile Money Movement: Catalyst 9. Although device innovation gets the majority of attention, to Jump-Start Emerging Markets.� Innovations: Technology, larger developments, such as cloud computing or network Governance, Globalization 6, no. 1: 101–17. standard negotiations, could serve as the underlying infra- GSMA Mobile Money Tracker. 2012. “Global Mobile Money structure for mobile money. Deployment Tracker.� Available at http://www.wirelessintelli- 10. However, high-profile disputes around the program in gence.com/mobile-money. December 2011 emphasized the clashes that are likely to IFC (International Finance Corporation). 2011. Mobile Money Study emerge with large-scale biometric programs. 2011. Washington, DC. http://www.ifc.org/ifcext/globalfm.nsf/ 11. Although international remittances are expected to become Content/Mobile+Money+Study+2011. increasingly important to the mobile money landscape, it is Kendall, Jake, and Bill Maurer. 2012. “Understanding Payment Behav- essential not to lose sight of the opportunity presented in the ior of African Households: A Vast and Untapped Market.� market for domestic remittances. Kendall and Maurer (2012) http://pymnts.com/commentary/Tips-for-2012-Understand- document nationally representative surveys of eight African ing-Payment-Behavior-of-African-Households-A-Vast-and- countries and “a vast and untapped domestic payments market� Untapped-Market/. 72 Information and Communications for Development 2012 Kendall, Jake, Bill Maurer, Phillip Machoka, and Clara Veniard. Pickens, Mark. 2011. “CGAP Releases Agent Management Toolkit.� 2011. “An Emerging Platform: From Money Transfer System to CGAP Web log post (February). http://technology.cgap Mobile Money Ecosystem.� Innovations: Technology, Gover- .org/2011/02/10/cgap-releases-agent-management-toolkit/. nance, Globalization 6, no. 4: 49–65. Porteous, David. 2007. “Just How Tranformational Is M-Banking?� Lochan, Rajiv, Ignacio Mas, Daniel Radcliffe, Supriyo Sinha, and FinMark Trust. Naveen Tahilyani. 2010. “The Benefits to Government of Sen, Soham, and Vikas Choudhary. 2011. “ICT Applications for Connecting Low-Income Households to an E-Payment Agricultural Risk Management.� ICT in Agriculture Sourcebook, System: An Analysis in India.�Lydian Payments Journal no. 2 259–84. Washington, DC: World Bank. http://www (December). http://ssrn.com/abstract=1725103. .ictinagriculture.org/ictinag/sites/ictinagriculture.org/files/ Maimbo, Samuel, Tania Saranga, and Nicholas Strychacz. 2011. final_Module11.pdf. “Facilitating Cross-Border Mobile Banking in Southern Stuart, Guy, and Monique Cohen. 2011. Cash-In, Cash-Out: The Africa.�Africa Trade Policy Note 1, World Bank, Washington, DC. Role of M-PESA in the Lives of Low-Income People. Financial Mas, Ignacio. 2011. “Three Enemies and a Silver Bullet.� Web log Services Assessment. post. Mobile Money for Unbanked. GSM Association (March 9). Suri, Tavneet, and Billy Jack. 2011. “Risk Sharing and Transaction http://mmublog.org/blog/three-enemies-and-a-silver-bullet/. Costs: Evidence from Kenya’s Mobile Money Revolution.� Mas, Ignacio, and Daniel Radcliffe. 2010. “Mobile Payments Go Working paper. Massachusetts Institute of Technology, Viral: M-PESA in Kenya.� In the “Yes Africa Can: Success Cambridge, MA, and Georgetown University, Washington, Stories from a Dynamic Continent� series. World Bank, Wash- DC. http://www.mit.edu/~tavneet/Jack_Suri.pdf. ington, DC (March). http://ssrn.com/abstract=1593388. USAID (U.S. Agency for International Development). 2010. Maurer, Bill, Taylor Nelms, and Stephen Rea. Forthcoming. Mobile Financial Services Risk Matrix. Washington, DC. http:// “Bridges to Cash: Channeling Agency in Mobile Money.� Jour- www1.ifc.org/wps/wcm/connect/14d0748049585fbaa0aab nal of the Royal Anthropological Institute. 519583b6d16/Tool+10.14.+USAID+MFS+Risk+Matrix.pdf? McKay, Claudia, and Mark Pickens. 2010. “Branchless Banking MOD=AJPERES. 2010: Who’s Served? At What Price? What’s Next?� Focus Note WEF (World Economic Forum). 2011. Mobile Financial Services 66, Consultative Group to Assist the Poor, Washington, DC. Development Report. http://www.weforum.org/issues/mobile- Morawczynski, Olga. 2009. “Examining the Usage and Impact of financial-services-development. Transformational M-Banking in Kenya.� In Internationaliza- World Bank. 2010. “At the Tipping Point? The Implications of tion, Design and Global Development, ed. Nurgy Aykin, Kenya’s ICT Revolution.� Kenya Economic Update, Edition 3, 495–504. Berlin: Springer. Washington, DC (December). http://siteresources.world- Morawczynski, Olga, and Sean Krepp. 2011. “Saving on the bank.org/KENYAEXTN/Resources/KEU-Dec_2010_Power- Mobile: Developing Innovative Financial Services to Suit Poor point.pdf. Users.� The Mobile Financial Services Development Report, 51–58. Washington, DC: World Economic Forum. Mobile Money for Financial Inclusion 73 Chapter 5 Mobile Entrepreneurship and Employment Maja Andjelkovic and Saori Imaizumi iven its strong recent growth, the global mobile health, agriculture, and financial services), supporting G industry is now a major source of employment opportunities on both the supply and demand side. Employment opportunities in the mobile industry can overall employment numbers in an economy. The greatest potential for employment growth therefore derives from demand for services enabled by mobile phones. For many be categorized into direct jobs and indirect jobs, with a entrepreneurs in developing countries and rural areas, a diverse labor force supplying each category. Direct jobs are mobile device is a tool not only for contacting customers created by mobile operators and manufacturers in profes- and accessing the internet, but also for making financial sions that range from engineers to managers to sales support transactions, establishing a client database, or coordinating staff. The International Telecommunication Union (ITU) just-in-time supply-chain deliveries. Such critical business estimates that around 1.5 million people are directly functions can enable small firms to thrive in locations employed in the industry worldwide (ITU 2011). The total where accessing markets or selling new products would number of jobs fitting this narrow “direct� description may otherwise be impossible. It is difficult to estimate the continue to grow slowly but may begin to decline as the number of people establishing new companies or the industry becomes commoditized. Indirect jobs, however, employment generated as small and microenterprises show strong potential for new growth, in professions expand, but mobile phones undoubtedly contribute to this broadly associated with the industry such as application process. development, content provision, and call center operations. It is also difficult to say with certainty how much the Indirect jobs can be created by mobile operators and manu- mobile communication sector has contributed to employ- facturers as well as by third-party content and device ment and entrepreneurship to date, because no global count producers, including entrepreneurs. In some emerging exists. It seems clear that the sector is a net generator of jobs, markets, outsourcing of mobile content development can however, even though it can occasionally eliminate employ- also create significant numbers of indirect jobs. In India ment opportunities. For example: alone, the mobile industry is expected to generate around 7 million indirect jobs during 2012 (COAI 2011). • In the United States alone, the mobile app industry This report argues that faster mobile networks and provided an estimated 466,000 jobs in 2011 with annual more capable smartphones make mobile communications growth rates of up to 45 percent from 2010 to 2011 a platform for innovation across different sectors (such as (TechNet 2012). 75 • In Canada a large proportion of mobile apps are used to young firms and entrepreneurs.5 The rise of entrepreneurship deliver games to handheld devices. The gaming sector is in the mobile industry is therefore unsurprising. The lack of expected to expand by 17 percent over the next two years, vertical integration and direct competition between opera- driven by proliferating mobile broadband access; as a tors, handset manufacturers, and content providers has result, mobile games are likely to generate a greater resulted in a complex environment of different technological number of employment opportunities. Of the 348 standards and innovation in business models, with ample gaming companies in the country, 77 percent expect to space for growing new businesses. New information-sharing hire new graduates in 2013 (Secor Consulting 2011). and collaboration practices that transcend the closed commu- nication channels are characteristic of newly establishing • Mobile money schemes have generally proved to be net markets. Rapid information flow dynamics were present in generators of jobs. Safaricom’s M-PESA system supports the early stages of other high-tech industries, including the 23,000 jobs for agents in Kenya alone.1 Airtel Kenya, the semiconductor industry in the 1970s, PC software in the second-biggest mobile operator, plans to recruit some 1980s, and the internet in the 1990s. 25,000 agents for its mobile money service, Airtel In today’s open innovation model, partners, customers, Money.2 researchers, and even competitors are finding new ways to • By boosting access to information about market demand collaborate in the product development process. The para- and prices, mobile phones can also improve conditions digm of open innovation assumes that firms can, and for entrepreneurship.3 A number of studies have shown should, use external as well as internal ideas and paths to that cell phones make entrepreneurial ventures less risky, market as they seek to advance their technology.6 Today, in mainly by reducing information search costs.4 many sectors there is a need to complement internally oriented, centralized approaches to research and develop- This chapter showcases some of the mechanisms by ment (R&D) with more open, networked methods, because which the mobile sector can support entrepreneurship and useful knowledge has become more dispersed (both within job creation, with the aim of informing policy-makers, and outside firms), while the speed of doing business has investors, and entrepreneurs themselves. Some of these increased. Collaborative approaches to innovation also offer approaches share similarities with traditional donor initia- new ways to create value, especially in fast-changing indus- tives, but many are novel ideas for which the “proof of tries. To capitalize on fresh opportunities, innovators must concept� has been demonstrated only recently. In an indus- find ways to integrate their ideas, expertise, and skills with try evolving as quickly as the mobile sector is today, it is vital those of others outside the organization to deliver the result to tailor support to the local circumstances and to evaluate to the marketplace (Chesbrough 2003; Aldrich and Zimmer impact regularly. As a framework for entrepreneurial activi- 1986; Teece and Ballinger 1987). ties, the chapter examines open innovation, and considers One of the most promising areas for entrepreneurship is one particular way of supporting entrepreneurial activity in in mobile software applications, where the barriers to the mobile industry, namely, specialized business incubators, market entry for individual developers and small and or mobile labs. The chapter reviews mobile microwork and medium enterprises (SMEs) are generally low. Mobile apps the potential of the virtual economy, and then reverses the can be written by programmers working for device manu- lens to consider mobile phones as a tool for job seekers. facturers, network operators, content providers, or software Finally, it summarizes suggestions to support entrepreneur- development firms, and they can also be created directly by ship and job creation in the mobile industry. individual freelance professionals. In emerging, as in more developed markets, there is no “natural� place where appli- cations originate; for the most part, network operators and Open innovation and mobile device manufacturers provide their own apps, with other entrepreneurship apps supplied to market directly by developers. This room The rapid innovation in the mobile sector is creating uncer- for independence allows developers who also have entrepre- tainty and disruptive technological change, while lowering neurial ambitions to start their own apps-based businesses. barriers to entry and generating opportunities for small and Many SMEs and individual entrepreneurs in the developing 76 Information and Communications for Development 2012 world offer their services at competitive rates compared with One way to support jobs created through entrepreneurship those in rich countries, but the vast array of choices of plat- in an era of open innovation is through structured social forms and distribution models can be challenging to navi- networking events that can help define business opportuni- gate. For example, most apps for simple, low-end phones are ties, identify talent, and draw investment into the mobile written for SMS (short message service), while apps for mid- sector in emerging markets. Networking events can also graft range devices often rely on mobile internet access and may best practice lessons from the ground back into the develop- be written in Java or PHP programming languages. Smart- ment and donor communities. An early example of an infor- phone applications can be written for the proprietary Apple mal social networking organization is Mobile Monday iOS, BlackBerry, or Windows platforms, or for the open (www.mobilemonday.net), an open community platform of source Android, among other options. According to one mobile entrepreneurs, developers, investors, and industry survey, in 2011 developers used an average of 3.2 platforms enthusiasts. Mobile Monday fosters business opportunities concurrently, which was a 15 percent increase over 2012 through live networking events. It provides a space for entre- (Vision Mobile 2011). While this growth may be interpreted preneurs to demonstrate new products, share ideas, and discuss as an indication of low barriers to entry, it is, rather, a sign of trends from local and global markets. Founded in 2000, in the necessity for developers to hone skills in multiple plat- Helsinki, the community has grown to more than 100 city forms, because no one knows which of these platforms—if chapters and is managed by 300 volunteers around the world.7 any—will become dominant in the future. In other words, More narrowly focused organizations, such as Google developers choose to diversify their skills because the Technology User Groups (GTUGs) (www.gtugs.org), cater to market, at the moment, demands variety and flexibility. participants interested in a particular developer technology. Marketing and distributing dilemmas are especially chal- These groups provide training for developers using the open lenging: app stores based on operating systems compete with Android mobile platform, followed by minimally structured those managed by handset manufacturers and major global networking events.8 GTUGs vary in format, from a dozen brands, and programmers must decide which store, or people who may get together to watch a corporate video, to stores, will be most effective as a delivery vehicle of apps to large groups involved in product demos, lectures, and compe- their potential customers. titions dubbed “code sprints� and “hackathons.� Smaller, local networks have also been formed in many cities. For instance, Informal industry networks for mobile Nairobi-based AkiraChix provides networking and training entrepreneurship for women and girls unfamiliar with software design. It culti- The lack of formal information channels and uncertainty vates the careers of young developers of both genders by mean that mobile entrepreneurs must keep up-to-date with providing training in programming and mobile application changes in standards and industry developments, resulting development (box 5.1). In Nepal Young Innovations, the in frequent socializing and informal networking between group behind the Kathmandu-based organization Mobile mobile entrepreneurs and developers. Informal social Nepal, regularly hosts “bar camps�—open conferences where networks, consisting of acquaintances, mentors, investors as entrepreneurs and developers give presentations and provide well as other mobile entrepreneurs, or peers, serve three feedback.9 In Georgia the business social network “mTbilisi� distinct purposes in the development of new ventures— promotes corporate partnerships, coordinates online and in- discovering opportunities, securing new resources, and person events focused on incubating mobile start-ups, and obtaining legitimacy—all of which are necessary for the provides a space for testing new ideas and designs. This proj- survival of a young firm (Elfring and Hulsink 2003). Entre- ect aims to bridge the gap between online and mobile appli- preneurs may have initiative, an appetite for risk, creative cation concepts—such as eCommerce applications, virtual ideas, and business acumen, but they may also need comple- guides, informational bases, or search engines.10 mentary resources to produce and deliver their goods or services. Social networks are important sources of support Features and dynamics of informal networks of and knowledge and can provide access to distribution chan- entrepreneurs nels, capital, skills, and labor to start new business activities Mobile developers and entrepreneurs interviewed for this (Greve and Salaff 2003). report identified both informal gatherings and more Mobile Entrepreneurship and Employment 77 Box 5.1 AkiraChix AkiraChix hosts informal gatherings, workshops, and competitions for mobile developers and entrepreneurs in Kenya. In 2011 AkiraChix and iHub, a community of technology innovators in Nairobi, partnered to host AppCircus, a traveling showcase of the most creative and innova- tive apps. Twelve finalists were given the chance to pitch their mobile apps to an audience. The overall winner was Msema Kweli, who developed a mobile app that helps keep track of Community Development Fund projects. It uses data made available by the Kenyan govern- ment through its Open Data Initiative to track spending and progress by constituency. Users can then report and comment on different projects. The app can be adapted to increase trans- parency and accountability for any community or development project. The first runner-up, Martin Kasomo, developed Hewa App, a mobile cloud-based music marketing and distribution platform for Kenyan artists and record labels to sell their music online. The jury highlighted the ease of use of this app and its attempt to tackle the problem of local music distribution in Kenya. Third place was claimed by Bernard Adongo of NikoHapa for a customer engagement and promotions application for businesses, which relies on news-sharing and geolocation tools to build a customer community. Source: http://akirachix.com. structured social networking activities (as mentioned specific product or service; however, it is execution that above) as helpful to innovation and entrepreneurship in “makes or breaks� an app. Developers and entrepreneurs the development of mobile applications. Respondents tend to rely on their informal networks to identify poten- from Kenya, Nepal, and Uganda indicated that they are tial partners, mentors, or peers who can be consulted in initially cautious about sharing ideas and information but confidence and relied on to help move a viable product that they freely provide lessons and support once they are from mind toward market. Once collaboration is under established and have begun implementing their business way, individuals may come back to the network to talk ideas.11 Entrepreneurs may first test options for starting about their example of successful partnership and to share their own business within a circle of carefully selected challenges. In other words, the interaction pattern seems contacts. As a second step, during the planning stage, to circle from a group setting to one-on-one interaction entrepreneurs often mobilize a large, informal network of and back to the wider network. friends, colleagues, mentors, and other acquaintances, The rewards of networking usually greatly outweigh the since they may not know who exactly can help them risks. Many mobile entrepreneurs note that collaboration is (Berglund 2007). Information exchange in informal envi- essential, because few applications can be successfully ronments carries risks for fragile new businesses, includ- brought to market by a single developer, let alone expanded ing the threat of idea theft: promising ideas risk being to additional platforms and maintained afterward. Market taken over not only by peers and direct competitors but information, idea validation, and partnerships are among also by larger companies, which, instead of hiring the idea the most frequently cited rewards of participation in social generator to complete the work, may assign an internal networks, according to more than 80 percent of participants team to develop the project in-house. To mediate such risks, in our survey (figure 5.1). Access to finance (including small once the project design stage has begun, entrepreneurs amounts raised from friends and family) and mentorship choose smaller, trusted groups from a wider social network opportunities were other important rewards, listed by more to form product development teams. Entrepreneurs recog- than 60 percent of respondents. Finally, marketing support nize that without a plan for execution, an idea is irrele- is another benefit of participating in informal peer groups. vant. Many individuals may recognize demand for a On the risk side, more than 35 percent of respondents are 78 Information and Communications for Development 2012 Figure 5.1 Rewards and risks from entrepreneur participation in social networks a. Rewards b. Risks Marketing support 33% Loss of 7.4% focus Access to finance 62% Loss of 9.3% Mentorship 67% funds Partners 80% Loss of 27.8% time Idea validation 85% Idea Market information 38.8% 93% theft Source: Author interviews. Note: Risks and rewards as perceived by mobile industry entrepreneurs, based on a sample size of 54, split between Kenya, Nepal, and Uganda. concerned about idea theft, in particular by more established can be helpful in drawing out participants and broadening businesses; however, even these entrepreneurs recognize the the number and scope of conversations within the network. necessity of vetting or validating ideas with their peers and consider the risk of idea theft to be tolerable. Loss of time, Mobile incubators funds, and focus are concerns for 28 percent, 9 percent, and 7 percent of respondents, respectively. While the informal networks of mobile entrepreneurs and The marketing of mobile applications is typically the developers described above can provide many resources, biggest expense and also the activity about which developers including knowledge and connections to investors, demand are often the least enthusiastic. Developers often rely on for more formal, hands-on learning spaces and supportive partners or enterprise customers for all aspects of market- office environments is also strong.14 A typical business incu- ing, which, if executed poorly, can stall the adoption of an bator may house 5 to 20 start-up companies in a shared otherwise successful app. For small teams of developers space offering common office equipment and conference working on “mass market� apps, marketing strategies can facilities. Most employ a resident manager who coordinates include dissemination and awareness-raising through word business assistance, training, and other services, such as of mouth, Twitter, Facebook, email, and SMS. Successful business plan development; accounting, legal, and financial incubators, such as iHub Nairobi,12 act as useful “amplifiers� advice; coaching and help in approaching investors; market- of marketing efforts, because local media and investors tend ing; and shared services, such as administrative support. to follow their announcements and activities closely. Once a client or resident business is deemed financially Participants report that small groups (from 4 or 5 people viable, it moves its operations outside the incubator, enters up to 20) are the most helpful form of networking in the market, hires new staff, and expands its contribution to discussing ideas and execution. Larger groups can be too the economy (Lewis 2001). impersonal or too strongly driven by formal presentations. A number of incubators, or “labs,� focused on mobile As a result, many organizers (including Mobile Monday entrepreneurs have been established in emerging markets, Kampala13) use breakout groups to ensure more meaning- including Grameen Foundation’s AppLabs in Uganda and ful conversations at their events. Network sponsors can help Indonesia, and infoDev’s regional mobile applications labo- strengthen social networks by attracting well-known figures ratories, or “mLabs.� (figure 5.2; box 5.2). Launched over the or VIPs to the meetings, as much as by direct financial past five years, these labs are still in an experimental stage, support. Attracting respected experts to address attendees but they offer several early lessons. Mobile labs facilitate Mobile Entrepreneurship and Employment 79 Figure 5.2 infoDev’s network of mLabs mLab South Asia: Pakistan Software Export Board consortium mLab East Asia: mLab ECA: EIF (Pakistan) Saigon Hi-Tech (Armenia) Park consortium www.mlabeca.com (Vietnam) Five mLabs selected mLab Southern Africa: mLab East Africa: *iHub_ from 75 applicants Meraka consortium consortium (Kenya) (South Africa) www.mlab.co.ke www.mlab.co.za Source: infoDev Box 5.2 infoDev’s mLabs and mHubs In response to demand by local mobile entrepreneurs, the World Bank Group’s infoDev program, in collaboration with the Government of Finland and Nokia, has established a network of five mobile application labs, or mLabs, and eight mobile social networking hubs, or mHubs. In Armenia, Azerbaijan, Georgia, Moldova, Kenya, Tanzania, South Africa, Uganda, Nepal, Pakistan, and Vietnam, mLabs and mHubs facilitate demand-driven innovation by grassroots entrepreneurs, so breakthrough low-cost, high-value applications can be devel- oped. Each mLab is a technology-neutral physical space with testing facilities for developing the technical skills and business sense needed to build scalable mobile solutions into thriv- ing businesses that address social needs. As well as providing state-of-the-art equipment, the labs offer technical training and workshops, and they connect developers and entrepreneurs with potential investors, experts, and public sector leaders. The labs are complemented by eight mHubs, which focus on bringing together various stakeholder communities in the mobile industry and providing advice, mentorship, idea and product development competi- tions, and access to investors through regular informal events and conferences. Both the mLabs and mHubs are run and used by local communities working to increase the competi- tiveness of enterprises in mobile content and applications and are part of a wider mobile inno- vation program, seeking to develop talent and produce successful companies with strong growth potential. Sources: Examples of mLab and mHub activities can be found on select websites: mlab.co.ke | mlab.co.za | mobilenepal.net | akirachix.com. 80 Information and Communications for Development 2012 demand-driven innovation by grassroots entrepreneurs, so ideally, the incubator sits near or at the center of the value breakthrough low-cost, high-value apps can be brought to chain for mobile content creation and, in its role as an inte- market. Although specialized incubators are not unusual, grator, brokers essential partnerships with all key mobile those focusing solely on mobile app businesses are a recent ecosystem players (Vital Wave Consulting 2011). phenomenon. That presents both a challenge and an oppor- Even in developed countries, mobile incubators are a tunity, because lessons and best practices can be borrowed recent phenomenon. In the United States the prominent from related ventures, but ample opportunity exists to mobile incubator Tandem Entrepreneurs was launched in develop new formats tailored to the mobile sector. Ideally, 2011 to enable a group of experienced entrepreneurs to mobile labs should be designed in a way that enables them provide resources and mentorship to early-stage mobile to remain open and adaptable to their environment, so start-ups. The incubator also offers each resident company lessons can be incorporated continuously throughout the seed funds and a collaborative workspace in Silicon Valley.15 lab’s existence. As mobile services become more sophisticated and wide- Mobile lab managers identify their members’ greatest spread, the potential of mobile entrepreneurs to contribute to needs as start-up capital and opportunities to network with the economies of both developed and developing countries is mobile ecosystem players and other technology entrepre- likely to grow. Most businesses based around mobile app neurs. In addition, many mobile app entrepreneurs need technology are at an early stage of development but may offer specialized business training to understand the mobile enormous employment and economic potential, similar to ecosystem, market demand, or both. Further, because that of the software industry in the early 1980s. Supporting mobile app development needs a special set of technical abil- networking and incubation of entrepreneurs in this space is ities, many app developers need specialized technical train- an important way to ensure such potential is tapped. ing to continuously update their programming skills. Networking with local business professionals can enhance Mobile microwork the incubation experience, providing entrepreneurs with highly customized advice that can accelerate the growth of New employment opportunities in mobile communications their business. Mobile labs can offer a wide range of services, are not restricted to highly skilled developers and entrepre- including “business accelerators�—intensive training and neurs but can also extend to a relatively low-skilled labor direct mentoring meant to quickly increase the value of a force. “Microwork� refers to small digital tasks (such as tran- company and to help management develop a viable growth scribing hand-written text or determining whether two strategy. In poor or remote areas, virtual incubation— photos show the same building). Typically, such tasks can be business training, advice, mentorship, and networking over completed in a few seconds by a person without special skills a distance and without a dedicated workspace, as well as or training, but they cannot be readily automated. Workers links with knowledgeable diaspora members—can be are paid small amounts of money for completing each task. particularly helpful. The service offerings implemented by For such work to be broadly accessible to workers from any given lab or incubator should reflect the environment developing countries, it should be performed via mobile and characteristics of the region where it is located. These devices as well as PCs. The mobile microwork market is still characteristics often dictate the services that can be offered very much in its infancy, however (box 5.3). and the most likely mix of revenue streams. Incubators may Currently, microwork employs more than 100,000 be instituted as nonprofit organizations, for-profit compa- people and contributes to a virtual global economy valued nies (usually when they do not receive grant funding), or at $3 billion a year, according to a recent infoDev study foundations. The business models and legislation of a given (Lehdonvirta and Ernkvist 2011). To understand how a country usually dictate the most advantageous status for an mobile user may be able to tap into additional sources of incubator. Regardless of the regulatory environment, income, consider, for instance, the growing gaming indus- however, partners are essential to the ultimate success of a try, which enables online gamers to become microworkers mobile incubator through their support of the organiza- compensated in virtual game currency that can often be tions’ development and distribution efforts. That is because, cashed in for real monetary gains. Today’s online game Mobile Entrepreneurship and Employment 81 Box 5.3 Mobile microwork: JANA JANA, a service developed originally by Nathan Eagle as TxtEagle, relies on SMS to connect users to a wide range of more complex media and communication technologies. It also acts as an aggregator of microwork tasks and assigns workers tasks that can be completed on a mobile phone, including, for example, data entry, translations, and transcriptions. With the help of partnerships with 220 mobile operators in 80 countries, it then compensates workers with mobile money or airtime minutes. Source: www.jana.com. market is very competitive, with monthly subscription fees social networks, which is “vital to having a voice in the for some games nearing zero. Instead of charging players, modern world.�16 leading online game producers can earn revenue by selling Although third-party gaming services have existed for virtual currency to players. The players buy virtual goods more than a decade, the general microwork industry and value-added services inside the game using virtual remains relatively new and undeveloped, with mobile currency. Third parties—monetization service providers— microwork in an even earlier stage of development. And facilitate the exchange of real money into virtual funds. Two despite the relative simplicity of tasks required, microwork such monetization services providers, Gambit and TrialPay, faces the challenge of breaking down larger business proce- allow gamers to pay for purchases by carrying out micro- dures or analytical problems into smaller components that tasks. After completing assigned microwork, the player is can be executed by microworkers. This is a technical, as well paid in virtual currency, which can be traded for virtual as procedural, problem that warrants further research by the goods or converted to real money. development and business communities alike. A number of Because virtual workers come from a global pool, inter- new ventures are considering potential solutions, in the hope national microwork aggregators must be able to provide of entering a market that is likely to grow into billions of compensation in foreign countries. This is complex in any dollars a year over the next five years. Easier-to-use interfaces market, but it is especially challenging in developing regions, and better distribution channels are also needed, if mobile where traditional financial infrastructure can be limited. microwork is to prove a viable employment option for some Mobile money schemes, which are more advanced in devel- of the poorest and least educated workers in developing oping than developed countries, provide a viable option for countries (Lehdonvirta and Ernkvist 2011). payment for microwork via mobile phones (box 5.4). Leila Chirayath Janah of Samasource works with refugees Mobiles and recruitment in Dadaab, Kenya, who are paid for performing small tasks for Samasource’s clients, including Google and CISCO. She In many countries, coordination and information failures suggests that microwork may be a natural complement to arise between the demand and supply sides of the labor microfinance, noting that, whereas microfinance can enable market. While the demand for employment exists both in the entrepreneurs to operate small businesses serving local needs formal and informal sectors, information on recruitment is (such as producing chickens on a small farm), microwork often limited to those with a strong social network or access to allows them to reach beyond the local market and develop a job postings via the internet. The mobile phone can extend variety of skills. Samasource now facilitates virtual assistance this access to those job providers or job seekers for whom PCs via microwork, including for clients from the developed are an ineffective or unavailable channel of exchange. A world. Janah also notes that, while typical microwork tasks number of emerging business models are using mobile are not necessarily intellectually stimulating, they encourage communications for improving coordination and informa- interaction with technology and access to global online tion flows in the labor market. At least four such services are 82 Information and Communications for Development 2012 Box 5.4 Turning ideas into applications: “Mobile To Work� challenge Idea competitions can be an effective way to encourage creativity and identify the most prom- ising product blueprints in a quickly innovating industry. To harness mobile microwork for devel- opment, infoDev has organized the Mobile To Work (M2Work) challenge to developers to come up with fresh thinking on ideas for microwork tasks that could be commissioned remotely to create employment opportunities in the developing world. The challenge, published online on February 1, 2012, at www.ideasproject.com/m2work, attracted some 944 proposals by the April 2 deadline. Prizes, sponsored by UKaid and the Department for Foreign Affairs of the Govern- ment of Finland and worth up to $40,000, are being awarded to the best ideas. The overall winning proposal, submitted by Aadhar Bhalinge of India, suggests a smart rickshaw network to crowdsource maps at a very low cost in developing nations by employing fleets of rickshaw driv- ers to feed live traffic updates into a subscription service. The regional winners also will benefit from mentorship and a hackathon designed to turn the best ideas into functional applications. Source: www.ideasproject.com/m2work. already up and running: Babajob (India), Assured Labor Of course, such technology cannot fully replace the tradi- (Latin America), LabourNet (India), and Souktel (Middle tional interview process. Once employers become interested East and North Africa, as profiled in box 5.5). Two others, in certain candidates, they can access job seekers’ informa- Pakistan Urban Link and Support (PULS) and Konbit (Haiti), tion and then contact them directly for an interview. Use of have developed their systems and will soon start operating. SMS text messaging can be popular where its cost is signifi- Skilled, educated workers may already have access to exist- cantly lower than that of voice services; however, in multi- ing web-based job-matching services such as Monster.com, lingual environments with illiterate populations, calls and but job-matching services that are mobile-based will be even voicemail remain particularly valuable. more important for people without access to web-based serv- Perhaps the greatest impact of mobile communications ices. Mobile-to-web technology will be beneficial for people on jobs lies not so much on recruitment techniques, but with a certain level of skills and education (that is, basic liter- rather on the structure of employment. Beyond creating acy) but not enough knowledge to create a marketable more vacancy notices, mobiles can stimulate entrepre- résumé or access online resources. Employers also find it hard neurial activity, as the demand for mobile industry hubs to identify low-skilled workers for entry-level jobs in devel- and mobile incubators has shown, and it can create many oping countries, because existing job-matching services more opportunities for self-employment, part-time work, mainly target highly skilled candidates. Mobile-to-web tech- and flexwork. In a mobile-driven economy, second and nology promises to bridge some of these gaps. third jobs will become much more common—and much Building trust among users is the most challenging task more important. for the job-matching business. Each of the new organiza- tions mentioned above offers additional and customized Conclusions and considerations services to meet the specific needs of local users, including for policy-makers interview, résumé writing, and networking skills training for job seekers, and access to a special database for employers. Overall, the rise of mobile technology carries great potential Depending on the job seeker’s target market and country of for employment, but with increased reach of powerful and operation, mobile phones may be used for different aspects affordable mobile devices, jobs may also be lost. Mobile of the job-matching business process. Most of these organi- technology can occasionally eliminate jobs, especially where zations use mobile phones for registration and job-match efficiencies are created or resources made available that notifications for job seekers. The actual job-matching ser- replace human input. For example, as more individuals vice is conducted mostly via web-based databases. acquire their own mobile phones, the demand for “village Mobile Entrepreneurship and Employment 83 Box 5.5 Business processes for job seekers and employers: Souktel’s JobMatch JobMatch find the perfect match. on your mobile phone. Job Seekers Employers 1 Sign Up 1 Register Right from your mobile phone, by Using your mobile phone or secure texting “register� to 37191. website. 2 Create Mini-CV 2 Create Mini-job Ad Use your phone to create an SMS Create a simple job ad on your phone “mini-CV� and upload it to our main or online. Upload to the main Souktel database, so hundreds of employers database, so thousands of job-seekers can find you. can find it and call you. 3 Browse Jobs 3 Browse CVs Browse thousands of jobs via SMS on Browse thousands of CVs by phone or your phone, or find the exact job that web, or find the exact CV that matches matches your CV info. Get employer the criteria of your job. Get job-seeker phone numbers for follow-up. details, along with phone numbers for follow up. Founded in 2005 by graduate fellows at Harvard University, MIT, and the Arab-American University of Jenin (West Bank and Gaza), Souktel launched a trial service in 2007. Within a year, over 100 of the 400 new college graduates who participated in the pilot found work or internships, and more than three-fifths of employers who used this service cut their recruiting time and costs by up to half. With a $100,000 grant from the World Bank Group, the service has been launched at three more college campuses in partnership with the Ministry of Educa- tion, then franchised in Morocco, Somalia, and the United Arab Emirates; and it is expected to launch in the Arab Republic of Egypt and Rwanda. Leveraging the high penetration rate of mobile phones, Souktel developed a job informa- tion software platform to connect job seekers with employers via a mobile device. One of the unique characteristics of Souktel is its franchise business model. Souktel has used this model to achieve a rapid growth in new markets. Each country uses a customized version of the JobMatch platform for a franchise fee and a recurrent annual support fee. In return, per-use revenue from local user fees charged to job seekers and employers accrue to the franchisee, helping to ensure each franchise’s long-term cost coverage and sustainability. As a way of measuring its impact, Souktel uses weekly database tracking of service use (searches, match requests, job alerts); monthly phone surveys of “matched� job seekers and employers; and bi-annual “match retention� phone surveys and institutional partner surveys. Positive outcomes are observed in the reduction of time spent looking for employment (from an average of 12 weeks to 1 week or less), wage increases (64 percent of matched job seek- ers in the West Bank and Palestine surveyed in 2009 reported a 50 percent increase in aver- age monthly wages, from $500 a month to $750 a month), and a reduction in hiring costs and time (70 percent of West Bank and Gaza employers surveyed in 2009 reported a 50 percent reduction in hiring costs and time, while 75 percent of the same sample confirmed a mean 5 percent increase in annual profits). Challenges have included working with the different mobile carriers. The cost of SMS, which averages about $0.05 a message in the West Bank and Gaza, is also a barrier to wider usage. Sources: Author interview and http://www.slideshare.net/guest923d97/souktel-jobmatch-overview. 84 Information and Communications for Development 2012 phones,� teleshops, and other phone-sharing services may • Investing in better mobile platforms for recruiters and disappear in many countries (matching the demise of public job seekers as well as platforms that extend work beyond payphones in many countries, following the widespread traditional work spaces and times adoption of mobile phones), taking away with it an impor- To capitalize on the potential of mobile technologies to tant source of jobs. In sum, however, with growing mobile support entrepreneurship and employment, policy-makers penetration rates, the mobile industry is widely expected to may consider whether current regulation supports an produce a net increase in jobs: enabling environment for mobile broadband and entrepre- • The direct number of jobs in the mobile industry from neurship, whether to provide financial support for entrepre- 1996 to 2011, as reported by governments to the ITU, neurs and incubation systems, and whether to incorporate shows a clear upward trend in most (although not all) some of the aforementioned tools in their public service countries (ITU 2011). offerings, such as schools and vocational training institu- tions, in order to increase employment opportunities in the • As the adoption of mobile technology increases, new jobs mobile ecosystem. are needed to support sales of prepaid cell phone minutes, mobile money transactions, and other mobile- based services. Notes • The introduction of mobile broadband is expected to 1. These could be considered part-time or supplementary jobs, generate significant revenues and jobs, especially in because M-PESA agent tasks are often combined with other related spin-off industries, including the development of merchant duties. http://www.safaricom.co.ke/index.php?id=252; mobile applications. http://www.bloomberg.com/news/2010-10-14/safaricom-of- kenya-will-boost-access-to-credit-insurance-for-unbanked- • Nontraditional business plans (such as those based on .html. microwork) are another source of potential growth in 2. Bharti Airtel took over Zain Kenya’s network in 2010. Some of jobs enabled by mobile technologies. the Bharti Airtel agents will also be M-PESA agents, but others will be new. • The labor market can benefit from the ability of mobile 3. Mobile Entrepreneurs in Ghana. http://www.webfoundation apps to improve efficiency and lower costs in matching .org/projects/mobile-entrepreneurs/ job candidates and employers. 4. As but one example, see Aker 2008. 5. This environment can be contrasted with one of stability, This chapter has outlined a number of tools for enabling continuity, and homogeneity of the more established econ- growth of employment opportunities in the mobile ecosys- omy. The link between entrepreneurship and economic tem, including: performance at the individual, firm, and societal levels has been shown in numerous studies that provide a framework of • Supporting informal community networks and activities dual causality between a strong period of entrepreneurship such as business competitions and hackathons to and a growing and rapidly innovating economy. See, for promote open collaboration, mentorship, and introduc- example, Audretsch and Thurik 2000, p 26, and Wennekers, tion of entrepreneurs and investors, and to identify viable Uhlaner, and Thurik 2002. new business ideas 6. The phenomenon of open innovation is explored, among other things, at Open Innovation Africa Summit, organized • Investing in mobile hubs and incubators, or mobile labs, jointly by infoDev and Nokia. The first two Summits were in order to equip entrepreneurs with updated technical held in Nairobi in November 2010 and in May 2012; see http://www.infodev.org/en/Article.640.html. skills, to provide them with tools necessary for product 7. www.mobilemonday.net. prototyping such as testing facilities, and to identify busi- 8. www.code.google.com. nesses with growth potential through business evaluation 9. http://www.younginnovations.com.np/. and acceleration programs 10. http://www.facebook.com/mTbilisi. • Facilitating creation of micro- and virtual work opportu- 11. Nairobi and Kampala interviews conducted by authors. See nities also Pfeiffer and Salancik 2003. Mobile Entrepreneurship and Employment 85 12. www.ihub.co.ke. Greve, A., and J. Salaff. 2003. “Social Networks and Entrepreneur- 13. www.momokla.ug/. ship.� Entrepreneurship, Theory & Practice 28 (1): 1–22. http:// 14. Globally, the shortage of employees with information tech- homes.chass.utoronto.ca/~agreve/Greve-Salaff_ET&P.pdf. nology skills has persisted in recent years. See, for instance, ITU (International Telecommunication Union). 2011. Yearbook of http://us.manpower.com/us/en/multimedia/2011-Talent- Statistics 2011. http://www.itu.int/ITU-D/ict/publications /yb/ Shortage-Survey.pdf. index.html. 15. http://techcrunch.com/2011/11/01/mobile-startup-incuba- Lehdonvirta, V., and M. Ernkvist. 2011. “Converting the Virtual tor-tandem-opens-new-�mobilehome�-in-silicon-valley- Economy into Development Potential.� infoDev. http://www now-accepting-applicants/. .infodev.org/en/Publication.1056.html. 16. http://www.socialedge.org/blogs/samasourcing/archive/2009 Lewis, D. 2001. “Does Technology Incubation Work?� Reviews of /08/25/microwork-and-microfinance. Economic Development Literature and Practice (Rutgers Univer- sity) https://umdrive.memphis.edu/jkwalkr1/public/business _incubator/do%20business%20incubators%20work.pdf. References Pfeiffer, J., and G. Salancik. 2003. The External Control of Organi- Aker, J. 2008. “Does Digital Divide or Provide? The Impact of zations: A Resource Dependence Perspective. Stanford: Stanford Cell Phones on Grain Markets in Niger.� http://www Business Books. .cgdev.org/ doc/events/2.12.08/Aker_Job_Market_Paper Secor Consulting 2011. Canada’s Entertainment Software Undustry _15jan08 _2.pdf. in 2011. A report prepared for the Entertainment Software Aldrich, H. E., and C. Zimmer. 1986. “Entrepreneurship through Association of Canada. http://www.secorgroup.com/files//pdf Social Networks.� http://papers.ssrn.com/sol3/papers.cfm? /SECOR_ESAC_report_eng.pdf. abstract_id=1497761. TechNet. 2012. “Where the Jobs Are: The App Economy.� Audretsch, D. B., and A. R. Thurik. 2000. “Capitalism and Democracy http://www.technet.org/wp-content/uploads/2012/02/Tech- in the 21st Century: From the Managed to the Entrepreneurial Net-App-Economy-Jobs-Study.pdf. Economy. Journal of Evolutionary Economics 10 (1): 17–34. Teece, D., and E. Ballinger. 1987. The Competitive Challenge: Strate- Berglund, H. 2007. “Opportunities as Existing and Created: gies for Industrial Innovation and Renewal. Cambridge, MA: A Study of Entrepreneurs in the Swedish Mobile Internet Harper and Row. Industry.� Journal of Enterprising Culture 15 (3): 243–73. Vision Mobile. 2011. “Developer Economics 2011.� http:// http://www.henrikberglund.com/Opportunities.pdf. www.visionmobile.com/rsc/researchreports/VisionMobile- Chesbrough, H. 2003. “The Era of Open Innovation.� MIT Sloan Developer_Economics_2011.pdf. Management Review 44 (3): 35–41. Vital Wave Consulting. 2011. “Mobile Applications Laboratories Busi- COAI (Cellular Operators Association of India). 2011. “Indian ness Plan.� infoDev. http://www.infodev.org/en/Publication.1087 Mobile Services Sector: Struggling to Maintain Sustainable .html. Growth.� Study commissioned from Price Waterhouse Coop- Wennekers, S., L. Uhlaner, and R. Thurik. 2002. “Entrepreneurship ers. http://www.coai.in/docs/FINAL_03102011.pdf. and Its Conditions: A Macro Perspective.� International Journal Elfring, T., and W. Hulsink. 2003. “Networks in Entrepreneurship: of Entrepreneurship and Education 1 (1): 25–68. The Case of High-Technology Firms.� Small Business Econom- http://people.few.eur.nl/thurik/Research/Articles/Entrepre- ics 21 (4): 409–22. http://www.ingentaconnect.com/content neurship%20and%20its%20Conditions_%20a%20Macro%20 /klu/sbej/2003/00000021/00000004/00403594. Perspective.pdf. 86 Information and Communications for Development 2012 Chapter 6 Making Government Mobile Siddhartha Raja and Samia Melhem with Matthew Cruse, Joshua Goldstein, Katherine Maher, Michael Minges, and Priya Surya overnments around the world, in varying A typology of mGovernment G stages of economic development and with diverse technological and institutional capaci- ties, are adopting or investigating mobile government Mobile government involves using mobile tools to change either the interactions between users and government or the processes of government. In 2012 tools in use include mobile (mGovernment). Several examples of how civil society, the networks (such as broadband, Wi-Fi, and voice-centric), private sector, and entrepreneurs are delivering service mobile devices (tablets, smartphones, featurephones), their improvements using mobile tools have been discussed in associated technologies (voice calling, SMS text messaging, chapters 2–5. This chapter focuses on how mobile tools are location detection, internet access), and software in the form helping governments to deliver public services more of network services and applications. widely and to improve processes of governance. Mobile government matters because it has the potential Yet, the mere introduction of mobile tools cannot to liberate users from the physical or location-related serve as a panacea for structural deficiencies in govern- constraints inherent in conventional service delivery and ments’ capacities or processes. Initial experiences suggest traditional electronic government (eGovernment) services. that the benefits of mGovernment will likely accrue to With more than 6 billion mobile telephone subscriptions those governments that put in place policies and worldwide in early 2012, and more than four-fifths of the programs that not only enable technological transforma- world’s population covered by mobile telephone networks, tion but also promote needed institutional reforms and mGovernment can make public services and processes avail- process redesign. The increased demand for services and able and accessible just about anywhere, at anytime, to governance stimulated by this technological transforma- almost anyone. tion will require an increased capacity to supply those Table 6.1 summarizes three forms of mGovernment. services and improve governance. Recognizing the rapid Typically, governments adopt a combination of these three evolution of the field, this chapter identifies some emerg- types to achieve their service delivery and governance objec- ing best practice policies and programs that could tives, and in so doing, provide accountability, transparency, support the technological transformation and needed and responsiveness to their citizens. First, mobile tools can institutional capacity development to unlock the benefits be used to supplement existing eGovernment applications of mGovernment. 87 Table 6.1 Three types of mGovernment mGovernment Supplement Expand Innovate Definition Mobile tools add a channel to Mobile tools allow conven- Mobile tools are used to develop existing eGovernment services tional services to reach previ- new services for service delivery and processes. ously un- or underserved and governance. constituents. Example The Republic of Korea with Bangladesh’s Health Line In the Democratic Republic of widespread e-Government, provides citizens with medical Congo, mobile tools allow citizens has added wireless portals and advice through a telephone to participate in budgeting, by interfaces to e-services (such hotline, cutting travel time and voting on how to spend local as transport tickets, renewals, waiting at health centers.b budgets.c confirmations).a Opportunities Mobile devices, which are Widespread mobile tools allow Combined innovation in technol- more widespread than tradi- conventional services to reach ogy and government processes tional computers, connect previously excluded citizens creates new opportunities for citi- more citizens to existing including the poor, rural popu- zens to engage with and hold e-services. lations, and people with government accountable. disabilities. Limitations Full advantage is not taken of Benefits are limited by the Extent of innovation depends on unique capabilities of mobile design and nature of the local political, economic, and tools (such as location deter- conventional service and capacity constraints; might need mination, built-in cameras); institution; do not necessarily more time to deploy. limited to existing eGovern- improve the government-citizen ment services. relationship. Implications for government Marginal: related to being able Moderate to significant: Significant: needs changes to to provide any related “physi- government capacity needs to government processes, creating cal� service at the needed grow to serve more citizens; response capacity. location and time. may need process re-engineer- a. http://www.futuregov.asia/articles/2011/mar/21/korean-city-opens-mobile-app-centre/. b. http://healthmarketinnovations.org/program/healthline-bangladesh. c. http://wbi.worldbank.org/wbi/news/2012/02/17/mobile-enhanced-participatory-budgeting-drc. based on traditional personal computers (PCs), adding a they allow participatory budgeting1 and community mapping new channel to reach citizens or manage processes of gover- of infrastructure and services.2 Experiments in mobile-enabled nance. Supplementary mGovernment adds the dimension of mapping by urban slum dwellers, for example, suggest that mobility to existing electronic services. innovative mGovernment could actually transform govern- Second, mobile tools can expand the reach of conven- ments’ design process for urban development programs by tional public services or government processes to citizens directly involving beneficiaries.3 Possibilities like these have who are unserved or underserved, often because of their profound implications for innovative mGovernment. remote location or the nonavailability of PCs and internet Although the specific form of a service will vary depending access. Broad mobile coverage and widespread access to and on the availability or advancement of technology, govern- familiarity with mobile telephones, give governments the ments could use these different types of mobile services opportunity to reach people who might not otherwise have regardless of the technical base or socioeconomic status. In easy access to these public services and processes. These two the case of transformative mGovernment, for example, appli- types—supplementary and expansionary—are also instru- cations using smartphones or basic devices can allow citizens mental, focusing more on the “mobile� in mGovernment. to report nonemergency municipal problems, track respon- Third, mGovernment can use the introduction of mobile siveness, and participate in virtual social spaces to put pres- tools to innovate new ways for governments to interact with sure on municipalities to address community issues.4 and involve constituents, creating new types of services and There are some limits on what might be possible to governance processes. Innovative mGovernment programs accomplish on a mobile device with a smaller screen or less intend to change not only the technology of interaction but powerful computing capability than a traditional personal also the nature of service delivery or the process. For example, computer has; more traditional eGovernment services will 88 Information and Communications for Development 2012 thus continue to have an important role. Both the design of nongovernmental organizations, private firms, and public mobile devices as well as their (and networks’) capabilities agencies are experimenting with and using mobile applica- are constantly evolving, however, and the future might see tions and services in interesting ways (OECD and ITU 2011; more powerful mGovernment services working alongside, UNDP 2012). As the frontier of innovation begins to touch or as replacements for, traditional eGovernment services. many public services, it often compels or encourages Governments will thus need to consider carefully which governments to experiment with these technologies. services can make the transition to mobile, weighing the Third, individuals have begun to harness these technolo- capabilities of both users and technologies in the process. gies and applications to voice their demands, mobilize communities, and engage with various levels of govern- ments (box 6.1). Even if the results of such efforts vary,5 Drivers for mGovernment combined with ongoing global political and economic Why have local, provincial, and national governments and transformations in recent years, this voiced demand for public agencies around the world become interested in responsive services and good governance by citizens through mGovernment? Experience thus far suggests that two sets of alternative means has increased pressure on some govern- factors are driving governments to look at mGovernment: ments to respond. global developments that create the environment for Because these developments affect different governments governments to consider mobile tools, and the opportunity in different ways, the speed with which governments adopt mGovernment offers to governments seeking to improve mobile tools is certain to vary. Yet, as the subsequent exam- service delivery and promote good governance. ples illustrate, few governments at any level anywhere in the world are not interested in going mobile (OECD and ITU Global developments 2011, 119–50). Three sets of global developments are creating an environ- ment in which mGovernment has become relevant. These The opportunity of mGovernment are the creation of the underlying technology base in the In comparison with the growing volume of evidence on the form of mobile networks and devices, deepening innovation benefits of eGovernment (infoDev 2009; Hanna 2010), the in mobile applications and services, and shifts in the ability impact of many mGovernment services is still unknown. of citizens to voice their demands using these technologies Even without clear evidence of the benefits, many govern- combined with increasing pressure on governments to ments nonetheless have begun to explore the possibility of respond to those demands. mGovernment if only in low-risk or limited ways. A small First, as chapter 1 shows, mobile networks are spreading number of governments are undertaking major efforts to even as devices become ever more capable. Mobile networks mainstream mobile tools in service delivery and governance. now have the capacity to deliver a mix of voice, audio-visual, This section describes some of the more sector- or function- and data services, creating an opportunity for governments specific examples first, beginning with a discussion of citi- to reach more citizens and offer new services through other zen-facing examples and following with examples of internal than conventional means. And while the vast majority of the process-oriented tools. It then discusses broader and, in world’s population now uses basic mobile telephones, more some cases, government-wide initiatives. powerful mobile devices such as smartphones and tablets are being increasingly adopted (Hellstrom 2008). Sector- or function-specific programs. There are many Second, as illustrated in chapters 2–5, there is tremen- examples of sector- or function-specific mGovernment dous growth in innovation in the development of applica- programs. The simplest ones use mobile tools as a means for tions and services that use mobile technologies. While government to reach citizens to provide information or initial innovation focused on commercial and entertain- simple services or to coordinate internal processes. ment applications, more recently there has been a rapid Common examples are emergency notifications for increase in innovative mobile applications and services for adverse weather events or for changes to water or energy social or economic development (Qiang et al. 2012a, b). A supplies. Moldova’s Ministry of Agriculture and Food Indus- growing list of individuals, cooperatives, not-for-profit and tries is working with a local agriculture cooperative to pilot Making Government Mobile 89 Box 6.1 The mobile telephone as a tool for citizen voice and empowerment Mobile devices, especially mobile telephones, have become important tools for citizens to express their opinions, mobilize groups, and report on events as they unfold (UNDP 2012). Although mobile telephones and associated applications cannot substitute for community mobilization and democratic processes, they can and have played a role in organizing citizens, especially through social media such as Facebook and Twitter (Brisson and Krontiris 2012). Perhaps the best-known example is the Ushahidi platform, which emerged in Kenya in response to the violence that erupted after the 2007 election. Ushahidi has now become an open source platform that anyone may use to create an incident- Box figure 6.1.1 Screenshot of the original reporting system, by crowdsourc- Ushahidi mash-up ing information using multiple channels such as SMS, email, Twit- ter, and the web. The information is used to create a map of events to give users a visual image of event hotspots. It has been applied in circumstances as diverse as elec- tion monitoring, disaster recovery, and crime reporting. More recently, feature- and smart- phones have been used widely in the ongoing political changes in the Middle East. Citizens have collected and disseminated information during recent events in Egypt, for example, through mobile-based tools includ- ing SMS, and for users with more sophisticated devices, through Twit- ter and YouTube (see chapter 1). Sources: Stauffacher, Hattotuwa, and Weekes 2012; http://ushahidi.com/about-us; UNDP 2012. an adverse weather alert service for farmers.6 Similar exam- the conventional system, a paper notification might either be ples come from Malaysia and the United States, where SMS misplaced or misdirected by rent-seeking intermediaries. is used to alert citizens about limited drinking water supplies After a successful trial, this system, e-Purjee, was extended to or energy blackouts (OECD and ITU 2011). A number of about 200,000 farmers and all 15 of the country’s state- educational systems use SMS to provide students with owned sugarcane mills, and a feature was added alerting examination results. The state of Kerala in India has used farmers when their payment was ready. Sugar production SMS to send students examination results on request since rose 62 percent following the introduction of e-Purjee, and 2010, reducing the need to wait in queues.7 farmers are benefiting from a more transparent system.8 Mobile tools have also shown potential in cutting out Integration with mobile-based payment systems offers intermediaries while improving broader economic outcomes. consumers of public resources the opportunity to pay for In Bangladesh, sugarcane farmers now receive an SMS telling services anytime and any where and also simplifies revenue them when they should bring their product to sugar mills. In collection for governments. Many cities in Europe and the 90 Information and Communications for Development 2012 United States have integrated payment for parking or trans- time and money with SeeClickFix, a citizen-reporting tool port services into mobile applications. In Bangladesh that allows people to geo-tag nonemergency municipal students can also apply for their university entrance exami- issues, such as potholes or graffiti, with their mobile nations through SMS, reducing the need for them to travel phones.14 With more than 57,000 incidents reported and a to the university to submit an application. Fees are deducted 45 percent fix rate between January and October 2010 from the applicant’s mobile phone account. Following a across multiple cities, this application shows promise for successful pilot, 28 postsecondary educational institutions efficient and streamlined citizen-government interactions. implemented the system in 2010.9 Qatar’s Hukoomi service Public agencies are also using mobile tools to support allows citizens to access and pay for a range of services internal functions and to improve resource and program through their smartphone or computer, including utility management. For example, electricity companies are begin- bills and parking or traffic fines.10 Complaint reporting ning to use mobile networks to get real-time consumption through mobile-based SMS has also been expanding data from wireless-equipped smart meters.15 This will allow throughout the world. electricity networks and consumers to be better informed Mobile government efforts have made use of mobile’s about consumption patterns, enabling new tariff models. potential for wider citizen engagement and participation to Governments are beginning to use mobile tools to strengthen accountability and transparency in public ser- manage resources more efficiently. Liberia’s water resource vices and processes. These efforts are typically innovative, management plan seeks to improve access to the half of the because they often change the delivery or management of a rural population that does not have access to potable water. conventional service or process. For instance, the Depart- The public works ministry deployed 150 data collectors to ment of Education in the Philippines worked with the Affil- map all of its roughly 7,500 publicly accessible water points iated Network for Social Accountability in East Asia and the with a mobile geo-tagging and monitoring tool called Pacific to set up a website called checkmyschool.org. This is a FLOW (Field Level Operations Watch). The process gave government-to-citizen online and mobile-based interactive the ministry a visualization of the status of water points, tool that allows citizens to view pertinent statistics on local allowing an updated needs assessment and leading to more schools. The site includes budget allocations, teacher and effective resource allocation.16 textbook information, and test scores for about one-fifth of The possibility of using location sensing, either through the 44,000 schools in the country. It also gives local teachers global positioning systems (GPS) embedded in devices or by and parents a public place to post areas of concern that they using mobile networks, has also created new service possi- feel need to be addressed. All users are able to view the bilities. In the city of Cebu, in the Philippines, taxi drivers are government’s responses to these posts. Seeking to improve using GPS-enabled mobile phones to receive traffic data and education service delivery through transparent and account- dispatch information. The data is used to generate maps in able behavior by school staff, checkmyschool.org has real-time that identify areas with traffic congestion and to increased community participation and vigilance and generate traffic volume estimates.17 improved teacher behavior.11 Cities are also using mobile devices to monitor the status Municipalities and local police departments have begun of ongoing programs. Auckland, New Zealand, piloted a to use mobile tools to innovate and encourage citizen project with Municipal Reporter, a GPS-based handheld participation in incident and issue reporting and tracking. system that allows the city to monitor its employees and Guerrero, Mexico, was able to cut response times to citizen resources. The handheld monitors are saving the city more complaints from 72 hours to 24 hours using Citivox.12 This than over 30 person-hours a week on highway maintenance service provides real-time report management, crowd- work. Auckland is currently in the process of shifting all sourcing reports from people using mobile telephones to maintenance management to a GPS-based system. Such register complaints or opinions on everything from simple tools also can help monitor programs in difficult security or municipal issues to violent crimes. Follow-up by public climatic conditions. For example, similar technologies, using agencies has led to wider citizen participation in the serv- GPS-enabled smartphones, have been used in Afghanistan ice.13 Similarly, cities across the United States are saving to monitor the quality and progress of road construction.18 Making Government Mobile 91 It is also possible to embed unique identifiers in physical Such government-wide initiatives span the range from objects that mobile phones can recognize (Gartner 2011). having an overall mGovernment strategy for mobile services Such tools can allow citizens, for instance, to report a broken to creating facilities for multiple government agencies to use streetlamp or park bench; officials can then use the same to deploy services. Countries as diverse as Afghanistan, technology to monitor repairs. India,21 and the United States22 have been developing Civil society or international agencies have also used plat- mobile-specific strategies that address issues such as how to forms to support government service delivery by improving align activities across agencies, encourage innovation within efficiency and reducing waste. For example, UNICEF created an overall technical or process framework, and support the a mobile-based data collection tool called Rapid SMS (see development and delivery of services. Other countries have box 3.2 in chapter 3).19 In Hong Kong SAR, China, the Mobile incorporated mobility in their overall ICT strategies. For Field Inspection System enables inspectors to use touch- example, Singapore’s government has already deployed screen PDAs (personal digital assistants) to enter inspection more than 300 mGovernment services and has plans, as part information at the scene, as well as to review the results of of the Singapore eGovernment master plan to create “more past inspections. Inspectors can send their reports through feature-rich and innovative mobile services� between 2011 their mobile phones without going to the office. The PDAs and 2015.23 Similarly, the U.K. government has identified were designed for easy use to shorten the training time. mobile technologies as an area for attention in its Govern- Some of the benefits include an approximate 10 percent ment ICT Strategy of 2011.24 increase in productivity, a 1.5-hour daily timesaving per Some governments have also begun to create shared facil- inspection team, and elimination of duplicate work.20 ities that may be used by multiple agencies. These facilities The wide range of countries and sectors covered in this are similar to those run by private firms that offer news, short list of examples is evidence of the growing interest in entertainment, or information services. A number of and use of mobile tools by governments at different levels governments have developed shared services platforms that and in varying stages of economic development. These exam- give citizens access through a common entry point to a range ples also display a range of implementation arrangements. of services. Such platforms allow costs to be shared across In some cases, such as with FLOW in Liberia, projects have multiple agencies, consolidate demand for telecommunica- been initiated by single agencies. In other cases, multiple tions services, and focus human capacity. The governments partners come together to deploy the tool and respond to of Jordan25 and of the state of Kerala in India (see box 6.2), citizens’ demands. An example is SeeClickFix, where the for example, have implemented shared services platforms responsibility of complaint registration, traditionally a that deliver a wide range of SMS, interactive voice response government function, is shared between a private organiza- (IVR), or simple text-data services that citizens access using tion and the city municipality. Governments adopt these a short code. Among the less developed countries, the services because they involve and engage citizens in incident government of Afghanistan is also planning to set up a and problem reporting through a third party, building trust government-wide mobile services delivery platform, which and credibility. At the same time, such services also build will allow government services to reach the half of all Afghan pressure on governments to perform, opening government households that have mobile phones; for many the phone processes to public scrutiny. would become the first medium for regular interaction with the government.26 Government-wide initiatives. Apart from the many initia- In countries where smartphones are common, govern- tives coming through bottom-up efforts, a few govern- ments have begun to create points of entry such as mobile ments have also begun mainstreaming mGovernment in sites (the United Kingdom’s direct.gov, for example27) or a larger and more coordinated way, taking a top-down even government “app stores.� Such facilities allow approach in some cases. Some governments, such as that of citizens easy discovery, access, and use of mGovernment the state of Kerala in India (box 6.2), have started on such applications. In 2010 the U.S. government created such coordination relatively early; others such as the Republic of an app store with the intention of making it easy for Korea have evolved to realize the need for such coordina- citizens to access information and services using their tion (box 6.3). smartphones.28 92 Information and Communications for Development 2012 Box 6.2 Kerala’s mobile government program The southern Indian state of Kerala has a population of 33 million. Leveraging the wide use of mobile telephones, the Kerala State IT Mission (KSITM) leads a province-level mGovern- ment program. The objective was to allow equitable access and enable social impact by reaching people with mobile devices, rather than only those who are able to afford and access computer-based internet services. The centerpiece in Kerala’s m-Government architecture is a common service delivery plat- form (SDP) that integrates various channels such as voice, data, and SMS. The KSITM manages the SDP, supervising a private firm, MobMe, which set up the SDP. All government depart- ments can access the SDP to enable the cost-effective design, development, and deployment of various mGovernment applications. This arrangement avoids duplication of effort and cuts capital spending on stand-alone systems. By integrating with all telecommunication companies, the SDP eliminates the need for individual coordination by government agencies. The KSITM also provides technical assistance to public departments to design and launch mobile applica- tions. Services include a common “short code� for the government (citizens dial KERALA or 537252 to access services). The service has created an additional incentive for the govern- ment to offer services relevant to consumers, including citizen voting on a social reality show where village governments present their successes, posting scores for major exams, and processing movie and bus ticket reservations. The KSITM has also set up an electronic SMS (eSMS) gateway for various government departments to communicate throughout their own units and departments and across institutions. An interactive voice response system supports government customer service call centers and was used to conduct an energy availability survey. A Mobile Crime and Accident Reporting Platform has been used by Keralan police to enhance public safety and law and order. Now, the state is looking to adopt a mobile payments platform, so citizens can pay government fees from their handsets. The state continues to improve and scale up initial mobile applications, such as multimedia messaging service-based accident and crime reporting. Since its launch in December 2010, the program has involved more than 60 government agencies, facilitated more than 3 million interactions between the government and citizens, deployed at least 20 mGovernment applications, and captured some 200,000 photos for crime and accident reporting purposes. As the KSITM sees it, this is a start to shifting government- citizen interactions from “red tape� to a “red carpet.� Yet, the state faces various challenges in using mobile technology to create transformative change. Successful applications for citizen participatory monitoring and reporting remain elusive. Other key challenges are the low resource and process capacity of public agencies, which limit the ability of the state to respond or improve its accountability. Having such coordinated and broader approaches to choice of technical standards and providing facilities where mGovernment does not mean that governments should or needed. will need to stop bottom-up or innovative application development. Governments will need to encourage quick Challenges for governments deployment of innovative applications when the demand arises. Moreover, as the U.S. government’s draft federal Two key challenges for governments seeking to implement mobile strategy indicates, one size does not fit all, and there mGovernment are to enable the technology transformation will be a need to accommodate agency-specific programs. and to respond increased demand for services and good Such coordination should enable innovation by guiding the governance. Making Government Mobile 93 Box 6.3 Evolving toward coordination: the case of the Republic of Korea By 2011 government agencies in the Republic of Korea had launched more than 160 mobile applications covering internal processes, access to information, and public service delivery. Problems soon emerged, however, because the applications lacked a common framework. As a result, there was a redundant development of products, mismatch of technical standards across ministries and agencies, and the lack of a clear direction for budget priorities around mGovernment services. To address these challenges, the government in 2011 launched a five-year, $55 million strat- egy to integrate mGovernment, focusing on both internal processes and public services. This strategy establishes a common framework for developing simple mobile websites, hybrid websites customizable by operating system, and mobile applications. For each of the five years, the strategy sets priorities ranging from security to quality assurance and authentication, to the establishment of a mobile common data management system. It also provides a detailed guide to the user interfaces and experiences with mobile government websites. Enabling the technology and even manage mGovernment applications. Many transformation governments might face a shortage of talent in applications development, however, or might not easily find willing Governments that are interested in mGovernment will need partners. Such constraints might slow down mGovernment to ensure that mobile tools are widely available to citizens, efforts or increase costs if nonlocal resources have to be that public agencies are ready and able to adopt these tech- called upon. nologies, and that the ecosystem of applications and services developers is in place to deliver needed services. Simple mobile telephones are now commonplace across Creating institutional capacity the world, and mobile networks are widespread. However, Even if mGovernment gains widespread acceptance, governments will need to ensure that the populations or concerns remain about the increased demand for respon- geographies they wish to target are adequately covered. This sive services and good governance. It is thus important to issue is especially important if technology choices are more match technological progress with increases in institu- sophisticated—using feature- or smartphones, for exam- tional capacity and, depending on the scale of change, ple—because mismatches could keep citizens from accessing possibly to restructure government. Institutional capacity public services. is a greater issue with mGovernment than eGovernment Public agencies will also need to have the ability to adopt because of the wider reach of mobile tools and conse- these technologies. In many countries, that is likely to quently the larger number of citizens that likely would involve closing gaps in technological or human capacity, use such tools. ensuring financial sustainability, and overcoming political or True transformation needs governments to pay close bureaucratic resistance. These considerations are similar to attention to re-engineering processes, reforming institu- those seen for eGovernment services in the past, and indeed, tions, and creating an environment for greater accounta- such factors limited the adoption of many of those programs bility and transparency. Such major shifts often need and reduced their long-term impact. significant political leadership and capital to implement, Many developing country governments are not in a and they inevitably take time. At the very least, governments position to carry out mobile applications development on should have the institutional capacity in place to respond to their own, so it will be critical for them to work with part- citizen demands because the move to mobile exponentially ners in the private or nonprofit sector. In some cases, coun- increases the capacity for citizens to demand services and tries have local technology companies that could develop good governance. 94 Information and Communications for Development 2012 As Ben Berkowitz, the co-founder of SeeClickFix, Enabling a sustainable technological explains, “The most important part of the process is the transformation ‘fix.’ Without that, the incentive for participation disap- Create a strategy for mGovernment. A holistic mGovern- pears.�29 Echoing a similar sentiment, Lishoy Bhaskar, vice ment strategy or strategic framework can help governments president at MobMe—the implementer of the Kerala identify gaps in technology and human capacity, in financial shared service delivery platform—finds that many govern- sustainability, and in the applications development ecosys- ment officials in the developing world understand the tem. It can also help raise the profile of mGovernment, benefits of mGovernment but often hesitate to implement potentially leading to high-level political support. And it because “there is no one to fix the potholes even if they mGovernment programs should be aligned with broader are reported.�30 national development programs and strategies.31 Such a The risk in not responding is that citizens will quickly strategy could also define needed technology, service, and lose trust and interest in participating in mGovernment data standards; identify common facilities and resources to programs. This risk extends not only to those programs that be developed within the government; and look for oppor- propose to make governance transparent and accountable tunities for partnering with civil society, the private sector, but also to those where technologies are supposed to and entrepreneurs. The strategy could also define ways to improve service quality by reducing wait times or simplify- make these programs financially sustainable. It will be ing processes. If a government is unable to follow up on the important, however, to avoid restricting innovation and expansion of service—for example, by being unable to serve flexibility. Furthermore, coordination should not imply that the increased number of patients that show up at health clin- some types of sector- or function-specific systems should ics because of better information on medical conditions—it never exist independently; some services (such as in health risks losing credibility. or education) will have specific needs and might be justifi- ably separate in their implementation. Emerging best practices for going Enable innovation. Much of the development in mobile mobile applications and services worldwide has come from inno- How might governments respond to the challenges inherent vation by nongovernment agencies. Governments are in going mobile? Emerging best practices—summarized in often late adopters of this technology. Hence, there is this section and in table 6.2—suggest a range of actions much to gain from allowing such innovation to continue, governments could take to boost technological take-up and with governments encouraging innovation and working improve institutional capacity. with partners such as mobile networks, applications Table 6.2 Policies and programs to promote mGovernment Enabling a sustainable Strengthening institutional technological transformation capacity to respond Policies • Create a strategy for mGovernment • Enable shared responsibility in service • Enable innovation delivery • Make mobile technology accessible • Promote efficiencies in resource alloca- and affordable tion and management and in processes • Enable mobile payments • Build trust • Define standards for technologies and content Programs • Create shared facilities • Train government officials on strategic • Support content creation and use uses of mGovernment in local languages • Incentivize testing through iterative • Mobilize and train users processes, user-centric design, and • Support public-private partnerships risk-reduced innovation programs Making Government Mobile 95 developers, and civil society organizations to design and information and data they produce. Such information, when pilot applications. At the least, interested agencies within digitized and openly available, could facilitate the creation of government should be encouraged to move swiftly toward mGovernment services (box 6.4). implementing “quick wins� that demonstrate the validity of the approach and hence secure greater support among Create shared facilities. Some governments, such as those in other participants. Definition of technology standards Kerala state and Jordan, are creating shared facilities to and opening of government facilities (such as data centers develop, deploy, operate, and manage mGovernment ser- or data sets) will help direct such innovation and avoid vices. For citizens, such common facilities would make undesirable fragmentation of systems. Governments access simpler and more organized by enabling “single could also partner with universities and mobile networks windows� (Hellstrom 2008). For the government, these to develop skills among potential mobile application resources include the hardware and software needed to run developers. applications as well as the communication services to connect with users through mobile telecommunications Make mobile technology accessible and affordable. Govern- networks (such as text messages, voice minutes, data serv- ments will need to promote universal access and service for ices). These facilities could also include commonly used specific user groups where mobile networks have yet to tools to simplify development and deployment of mGovern- reach, especially because these groups also tend to be the ment services (such as survey tools, peer-to-peer communi- unserved for regular government services. Efforts should cation tools, short codes). Such shared facilities for also focus on improving the affordability of devices and mGovernment could also link with efforts to create govern- services. Some countries may be able to reduce the price of ment cloud-computing facilities.33 devices by cutting excessive taxes, duties, or levies. Service prices might be reduced by consolidating demand across Support content creation and use in local languages. As government, for example, through purchases of bulk SMS or with any technology, cultural context, user capability, and IVR minutes. The reader is directed to chapter 7 on this local relevance will drive adoption and success. Ensuring topic (see also Kelly and Rossotto 2012; Muente-Kunigami that mGovernment services remain focused on beneficiar- and Navas-Sabater 2010). ies is important, especially in the case of service delivery or information provision. Governments will need to engage Enable mobile payments. Many government transactions with a wide range of stakeholders—technologists, commu- involve the transfer of money to citizens or payment of fees nities, users, intermediaries, and public service providers— by citizens. Enabling mobile payments will allow citizens to to design and develop demand driven and user-centric make and receive payments securely, even if they do not have applications and services. Updated content will have to bank accounts or cannot securely carry cash, and will be created or kept in local languages, and the content and encourage them to use mobile-based services. The reader is the application will need to fit the needs and ICT literacy directed to chapter 5 for further discussion. levels of users. Adopt standards for technologies and content. Govern- Mobilize and train users. Users beyond early adopters need ments can help to enable innovation by adopting standards to understand the benefits of using mGovernment services. for technologies and content. For example, the Open 311 Community-level intermediaries can play a vital role in framework is a protocol developed by a combination of educating users and driving adoption of applications. government and civil society organizations and adopted by Critically, however, evidence of government responsiveness municipalities for location-based collaborative issue track- and improved service delivery and governance will be the ing.32 Adopting Open 311 could help standardize complaint most effective means to attract citizens to this platform. or issue management applications across government, making them interoperable. Such standards could also Encourage public-private partnerships to support extend to how government agencies open and share the mGovernment. Both private and public sector efforts will 96 Information and Communications for Development 2012 Box 6.4 Open data and mobile access in Kenya Governments are beginning to open public data sets and make them accessible to the public and civil society. With mobile telephones being more widespread than PCs, it is not surpris- ing to see more open data being made available on mobile platforms with interesting conse- quences. In July 2011 Kenya became one of the first African countries to launch an open data initiative, making some 160 government datasets open to the public, with more on the way (www.opendata.go.ke). The aim was to lead to a more responsive and citizen focused-government. Among the initial data sets that were uploaded are poverty surveys by district, budget by government department, and plans for future changes in electoral districts and health facilities. A beta site was launched in June 2009 and the public site a year later. But in Kenya, as in many other developing nations, mobile ownership far exceeds PC owner- ship, so to increase transparency and widen access, facilitating mobile access to the data is an important goal. Kenya’s experience with Ushahidi (see box 6.1) created a local precedent for this. To support the development of mobile applications that would open up the government data, the Kenya ICT Board launched the Tandaa Digital Content Grant, offering up to 30 awards totaling $1.5 million. An early success came when exam results were made avail- Box figure 6.4.1 Screenshot from Open Data able on mobile phones. Kenya website, showing poverty Providing data to citizens, civil and pupils per teacher society, and entrepreneurs will support their ability to engage with the government and help develop new ideas and services. As such, open data is part of making the government a platform on which stakeholders and constituents can engage, interact, and create. Source: Adapted from Rahemtulla et al. 2011. complement and strengthen each other. Initially, the private responsibility of managing the technology and sharing sector will focus on commercially viable applications some of the financial or political risks. including media and infotainment, mCommerce, and advertising- or subscription-based information services. Strengthening the institutional capacity to respond With the right incentives and given the opportunity, Enable shared responsibility in service delivery. A key private entities can supplement state technological capacity consideration is how the nature of service delivery will and create and deploy applications that serve public needs change as technology and its use evolves. It is difficult to or support program management. The examples of Kerala predict the extent of transformation in services. However, (see box 6.2), where the IT Mission has contracted with a governments can begin to prepare by looking for ways to private company, and of SeeClickFix, a private group work- share responsibility, which can also create the possibility of ing with municipalities, suggest such new possibilities. increasing capacity. Three options exist: governments could Such partnerships could also help close technological or transfer responsibility for service delivery to the private human capacity gaps, with private firms taking on the sector or civil society, share responsibility for serving citizen Making Government Mobile 97 demands with other actors, or continue to supply improved building programs to develop skills of government officials or enhanced services but with the help of private and civil to understand and use mGovernment tools. In Afghanistan, society actors. These models can exist side by side. For the Ministry of Communications and IT coordinates example, many countries have transferred responsibility for government training of chief information officers (CIOs) infrastructure construction and operation (roads, power, with targeted mGovernment-related training. It is also creat- telecommunications) to the private sector while retaining ing a team of mGovernment advisors—international or sharing responsibility in others areas such as education experts who could advise on strategic interventions—to or health services. In any case, governments will need to support the cadre of CIOs and officials keen to deploy consider how the re-engineering of processes could open mGovernment tools. new models for service delivery and remove any unneeded legal or regulatory impediments to transferring or sharing Incentivize testing, user-centric design, and innovation. responsibility where such models are valuable. Governments could consider promoting innovative approaches to applications development and operation Promote efficiencies in processes and in resource alloca- through innovation challenges or competitions;36 set up tion and management. Governments can encourage the incubators that provide entrepreneurs within and outside use of mGovernment tools by creating opportunities for government a physical, social, and intellectual space to greater efficiencies within existing workflows and develop innovative services; or support national innovation processes. In an analogous example, the government of policy programs. A forthcoming Innovation Support Bhutan encouraged civil servants to use electronic commu- Program in Afghanistan explicitly targets the development nications technology while cutting office stationery budg- of products for improved public service delivery and adop- ets.34 As was the case in Bhutan, adequate training and tion. Governments should also borrow from techniques capacity building will be needed to support the transition employed in the private sector for the development and to the use of mobile tools. adoption of new technology platforms and services, such as iterative, pilot-based service rollout, and user-centric design Build trust. One of the most critical, yet often ignored, to ensure relevance and usability. aspects in mGovernment is to balance the increased interac- tion between governments and citizens with the need to Conclusions ensure privacy and security. There are three aspects to this— the security of private information, avoiding the perception The ubiquity of the mobile telephone has created an oppor- of surveillance, and managing anonymity—which are tunity for governments around the world to improve serv- discussed in box 6.5. Legal and ethical views on privacy vary ice delivery and enhance governance. Mobile tools also from government to government and also depend on social create the opportunity for citizens to participate directly context. Yet, in every case, governments must maintain the and engage with governments like never before. Already, expected level of trust through a combination of legal and examples from a wide range of countries, provinces, and technical actions. Infringements must be dealt with quickly. cities are showing that mGovernment is taking hold and A related area for consideration is the development of elec- helping supplement, expand, and innovate services and tronic or mobile identification services to protect citizens’ governance. identities in their interactions with governments and to Mobile government is relatively nascent and the potential prevent data leakage and fraud. The government of Moldova of mobile devices continues to evolve, so new ideas are is now developing a system to create a unified way to solve, certain to emerge to help make governments mobile. Based for any electronic or mobile application, security-related on experience thus far, however, governments seeking to go tasks such as identity management, authentication, and mobile will need to create an enabling environment for tech- transaction authorization.35 nology transformation as well as the institutional capacity to respond to citizen requests for service. Train government officials on strategic uses of mGovern- In closing, any government seeking to adopt mobile ment. Governments will need to undertake some capacity- tools should keep in mind that this process will successfully 98 Information and Communications for Development 2012 Box 6.5 Challenges to trust and credibility As governments find more ways to deliver services using mobile and geo-location technolo- gies, concerns over security and privacy are mounting. If used properly, mGovernment can promote transparency and accountability of service delivery. However, citizens often express concern about the security of their private and confidential information, possible surveillance, and anonymity, among other issues. It is vital that governments create a legal and technical framework to protect data from corruption or leakage. Without strong protection or the quick resolution of any breach, citizens will be wary of sharing their information with the government, and efforts to connect and inter- act would quickly be undermined. Internet users already face security problems—for example, so-called “Trojans� or “malware� can compromise personal computers and gather private data from users illegally. While location- and context-based services offer powerful opportunities, illegal or unwar- ranted surveillance must also be avoided. Again, citizens need to be assured that installing applications or using services will not compromise their privacy. Governments will need to exercise care in securing their systems and software to avoid any perception of surveillance. For example, the Data Protection Working Party, an independent European Union advisory body on data protection and privacy, has suggested that users of smartphones and other mobile devices give clear and explicit consent and have a clear understanding of how the data will be used, before location data is collected. Finally, citizens might seek anonymity (or pseudonymity) as they become more vocal to avoid the risk of reprisals due to their views. Governments may need to consider which ser- vices require identification and which services (anticorruption hotlines, for example) might be more popular if citizens can remain anonymous when they make a report. Balancing privacy concerns against the government’s need to ensure that it is dealing with legitimate users of the service should not be a barrier to exploring mGovernment. Rather, it should be the catalyst for ongoing conversations regarding the strength of privacy laws and proper auditing alongside the ability to share information. Source: http://ec.europa.eu/justice/data-protection/article-29/documentation/opinion-recommendation/files/2011/wp185_ en.pdf. transform the government-citizen relationship only when resource allocation for urban services. See http://blogs governments enable the transformation of both elements— .worldbank.org/ic4d/node/535. “mobile� and “government.� 4. See, for example, http://seeclickfix.com/, http://www.fixmy street.com/, and http://plus1lab.com/about-cityreporter/. Notes 5. See varying opinions and views on the role of social media and ICT in recent political events: http://pitpi.org/index 1. “Participatory budgeting� implies citizen involvement in the .php/2011/09/11/opening-closed-regimes-what-was-the- budgeting and allocation of public resources through direct role-of-social-media-during-the-arab-spring/; democracy; see, for instance, http://www.youtube.com/watch http://www.twq.com/ 11autumn/docs/11autumn_Alterman ?v=hZYm0kEvkAo; http://www.tnpp.org/2011/12/mobile- .pdf; and http://www .time.com/time/world/article/0,8599, participatory-budgeting-dr-congo.html. 2104446,00.html. 2. www.mapkibera.org. 6. http://www-wds.worldbank.org/external/default/WDSCon- 3. Initial efforts toward this aim are under way in Dar es tentServer/WDSP/IB/2010/07/19/000334955_20100719024447 Salaam, for example, where citizens are involved in mapping /Rendered/PDF/530500PAD0IDA11B01OFFICIAL0USE01091 community resources as a first step toward improving .pdf. Making Government Mobile 99 7. http://www.hindu.com/2010/05/02/stories/2010050255260400 34. http://www.bhutanobserver.bt/ministries-try-frugal-stationery- .htm. use/. 8. http://www.epurjee.info/Implementation.php. 35. http://egov.md/upload/CN-mobile-eID-eGC-June-2011.pdf. 9. http://www.ictdata.org/2011/10/going-digital-in-bangladesh 36. http://whatmatters.mckinseydigital.com/innovation/prizes- .html. a-winning-strategy-for-innovation. 10. http://www.ictqatar.qa/en/department/national-programs/ e-government/hukoomi. References 11. www.checkmyschool.org. Brisson, Z., and K. Krontiris. 2012. Tunisia: From Revolutions to 12. http://citivox.com/. Institutions. infoDev. http://www.infodev.org/en/Publica- 13. http://thanassiscambanis.com/sipa/?p=276; http://www.infor tion.1141.html. mationactivism.org/en/citivox. Gartner. 2011. “Executive Advisory: The Untapped Potential of 14. http://seeclickfix.com/. Mobile: Connecting the Physical World to the Online World� 15. http://www.telenor.com/en/news-and-media/press-releases/ (April 27). http://www.gartner.com/id=1656117. Registration 2011/telenor-to-measure-your-electricity-consumption. required. 16. http://www.wsp.org/wsp/sites/wsp.org/files/publications/WSP- Hanna, N. 2010.Transforming Government and Building the Infor- FLOW-Liberia-QandA.pdf. mation Society: Challenges and Opportunities for the Developing 17. http://www.citynet-ap.org/images/uploads/resources/Dhaka World. New York: Springer. Nov27.pdf (p. 36). Hellstrom, J. 2008. “Mobile Phones for Good Governance: Chal- 18. http://aidc.af/aidc/. lenges and Way Forward.� Draft discussion paper. http:// 19. http://www.rapidsms.org/case-studies/malawi-nutritional- mobileactive.org/research/mobile-phones-good-governance- surviellence/. challenges-and-way-forward. 20. http://www.itu.int/ITU-D/asp/CMS/Events/2011/ict-apps/s1 infoDev. 2009. “eGovernment Primer: Using ICT for Public Sector _ITU_souheil.pdf. Reform.� http://www.infodev.org/en/Project.39.html. 21. http://www.mit.gov.in/content/framework-mobile-gover- Kelly T., and C. Rossotto, eds. 2012. Broadband Strategies nance. Handbook. Washington, DC: World Bank. www.broadband- toolkit.org. 22. http://mobility-strategy.ideascale.com/a/pages/draft-outline. Muente-Kunigami, A., and J. Navas-Sabater. 2010. “Options to 23. http://www.egov.gov.sg/c/document_library/get_file?uuid=4f Increase Access to Telecommunication Services in Rural and 9e71be-fe35-432a-9901-ab3279b92342&groupId=10157 (p. 7). Low-Income Areas.� World Bank Working Paper 178, Washing- 24. http://www.cabinetoffice.gov.uk/content/government-ict- ton, DC. books.google.com/books?isbn=0821381407. strategy. OECD (Organisation for Economic Co-operation and Develop- 25. http://www.jordan.gov.jo/wps/portal/?New_WCM_Context= ment) and ITU (International Telecommunication Union). /wps/wcm/connect/gov/eGov/Home/e-Government+Program 2011. “M-Government: Mobile Technologies for Responsive /E-Services/Shared+Services/SMS+Gateway. Governments and Connected Societies.� http://dx.doi.org/ 26. http://documents.worldbank.org/curated/en/2011/03/ 10.1787/9789264118706-en. 13995882/afghanistan-ict-sector-development-project Qiang, C. Z., S. C. Kuek, A. Dymond, and S. Esselaar. 2012a. (pp. 24-25). “Mobile Applications for Agriculture and Rural Development.� 27. http://www.direct.gov.uk/en/Hl1/Help/YourQuestions/ World Bank. http://go.worldbank.org/YJDV8U9L0. DG_069492. Qiang, C. Z., M. Yamamichi, V. Hausmann, R. Miller, and D. 28. http://apps.usa.gov/. Altman. 2012b. “Mobile Applications for the Health Sector.� 29. Interview with Mr. Berkowitz, June 2011. World Bank. http://siteresources.worldbank.org/INFORMA- TIONANDCOMMUNICATIONANDTECHNOLOGIES/Reso 30. Interview with Mr. Bhaskar, December 2011. urces/mHealth_report_(Apr_2012).pdf. 31. This is also noted in the draft mGovernment strategy outline for Rahemtulla, H., J. Kaplan, B-S. Gigler, S. Cluster, J. Kiess, and the U.S. federal government; see http://mobility-strategy.idea C. Brigham. 2011. Open Data Kenya: Case Study of the Underly- scale.com/a/pages/draft-outline. ing Drivers, Principal Objectives and Evolution of One of the First 32. http://open311.org/learn/. Open Data Initiatives in Africa. Open Development Technology 33. http://www.cloudbook.net/directories/gov-clouds/government- Alliance. http://www.scribd.com/WorldBankPublications/d/ cloud-computing.php. 75642393-Open-Data-Kenya-Long-Version. 100 Information and Communications for Development 2012 Stauffacher, D., D. Hattotuwa, and B. Weekes. 2012. The Potential and UNDP (United Nations Development Programme). 2012. “Mobile Challenges of Open Data for Crisis Information Management and Technologies and Empowerment: Enhancing Human Devel- Aid Efficiency: A Preliminary Assessment. ICT for Peace opment through Participation and Innovation.� http://www Foundation.http://ict4peace.org/wp-content/ .undpegov.org/sites/undpegov.org/files/undp_mobile_ uploads/2012/03/The-potential-and-challenges-of-open-data- technology_primer.pdf. for-crisis-information-management-and-aid-efficiency.pdf. Making Government Mobile 101 Chapter 7 Policies for Mobile Broadband Victor Mulas his final chapter looks to the future and provides have found a positive relationship between broadband pene- T policy recommendations for expanding the range and uptake of mobile applications for develop- ment. In practical terms, that means looking at the shift tration and economic growth, particularly in developing countries (Qiang and Rossotto 2009, 45; Friedrich et al. 2009, 4; Katz et al. 2010, 2; Digits 2011). One of the transmission toward mobile broadband networks. Broadband has a posi- channels of this growth is linked to the transformational tive impact on growth and development (Qiang and Xu effect of broadband throughout the sectors of the economy, forthcoming). Mobile broadband, in particular, is expected to raising productivity and efficiency (Kelly and Rossotto 2011). show an even higher positive effect on economic growth, Mobile broadband has been found to have a higher impact especially in developing countries. Thus, mobile broadband on GDP growth than fixed broadband, through the reduc- development and diffusion across the economy is a subject of tion of inefficiencies (Thomson et al. 2011). policy action. Unlike other information and communication Mobile telephony has already demonstrated that technology (ICT) services, such as fixed-line voice telephony, networks that use spectrum, such as mobile networks, are broadband (including mobile broadband) behaves as an often the most efficient infrastructure for expanding ICT ecosystem where the supply and demand sides interact and services worldwide, especially in developing countries, mutually reinforce each other. Hence, both aspects of the which generally suffer from a shortage of fixed infrastruc- ecosystem—supply and demand—need to be addressed by ture (see Statistical Appendix). Such is the case for broad- policy initiatives (Kelly and Rossotto 2011). Supply-side poli- band, which is now growing faster in developing cies aim at promoting and enabling the expansion of mobile countries than in developed ones, with a compound aver- broadband networks; demand-side policies seek to increase age growth rate of over 200 percent since 2009. In some adoption of mobile broadband services. Policy recommenda- countries, such as Colombia, Kenya, South Africa, and tions for both supply and demand are addressed below. Vietnam, mobile broadband is already the main platform for broadband access, having surpassed fixed broadband by over 10 times in the two African countries and almost The mobile broadband opportunity 3 times in Vietnam (figure 7.1). and developing countries Even so, the broadband gap between developing and As discussed in chapter 1, broadband has an important effect developed countries is increasing.1 Whereas around half on economic growth and development. Numerous studies of mobile connections provide broadband access in 103 Figure 7.1 Broadband subscriptions in selected Figure 7.2 Broadband as an ecosystem where countries per platform (mobile vs. fixed) supply and demand factors interact with each other 20 20 Penetration rates, percentage 15 14 SUPPLY 13 10 9 6 Pushes Pulls 5 supply demand 5 2 0.1 0 m bia a ca ny na fri lom Ke DEMAND et hA Vi Co ut So Mobile broadband Fixed broadband Source: World Bank. Sources: TeleGeography Inc. database, March 2011, and World Bank data- base for population data, Note: Data are for the third quarter, 2011, for Colombia, Kenya, and South Africa; second quarter, 2011, for Vietnam. With this framework in mind, policies to support and enable broadband diffusion through mobile networks can be categorized as either supply-side or demand-side developed countries, in developing countries this policies. percentage is below 10 percent. The different pace of mobile broadband adoption has many causes, one of Supply-side policies which has been more aggressive policies in developed Supply-side policies aim to expand mobile broadband countries to enable and foster the implementation of networks by addressing the bottlenecks and market failures mobile broadband technologies. As shown by examples in that constrain network expansion and by providing incen- Chile, Germany, Sweden, and the United States, to name tives for wider mobile broadband coverage. Bottlenecks and but a few, policies that foster mobile broadband allow for market failures differ among countries, and policy-makers its faster and wider diffusion. and regulators should assess their specific market condi- tions, prioritizing those policies that are relevant to their domestic bottlenecks and market failures. However, two Policy recommendations main bottlenecks are relatively common worldwide: insuffi- for facilitating mobile cient availability of spectrum, and inadequate backbone broadband diffusion networks. To understand how policy-making can promote and enable The following policy recommendations focus on these broadband, it is useful to understand the various elements common bottlenecks, as well as on incentives for expanding that influence broadband diffusion. By contrast with other the coverage of mobile broadband networks. ICT services, such as voice, broadband works as an ecosystem, where the supply and demand sides interact and reinforce Ensure sufficient availability of quality spectrum to deploy each other (Kelly and Rossotto 2011, 25). Thus, broadband cost-effective mobile broadband networks. Availability of diffusion not only requires the supply of access through spectrum may become a bottleneck to the development of network coverage expansion, but also the development and mobile broadband networks for various reasons. First, to facil- availability of demand-side enablers, such as affordable smart itate rapid deployment of these networks, operators need devices and content and applications that respond to user spectrum that is technically adapted to the most cost-efficient needs (figure 7.2). mobile broadband technologies. Technologies are designed to 104 Information and Communications for Development 2012 be more efficient in specific spectrum bands. International market spectrum of suitable and sufficient quality for these harmonization provides the benefits of economies of scale technologies. In some case, policy-makers and regulators for network equipment. As a result some bands are much may need to refarm spectrum (the practice of making spec- more commercially attractive than others. If spectrum is not trum available by moving existing users or organizing band offered for the bands where the most cost-efficient technolo- use more efficiently) and reassign legacy users with less gies work, operators have to opt for other less efficient valuable uses or less efficient technologies to other bands. options, which can result in more limited investments or no Permitting spectrum trading among operators also allows investments at all. for spectrum refarming for more efficient uses through Second, operators need spectrum in the bands that are private sector–led transactions. The digital switchover (the most effective for deploying mobile broadband technolo- process whereby analog television has been superseded by gies. For instance, a fourth-generation broadband mobile digital television) has allowed spectrum managers world- technology such as Long-Term Evolution (LTE) can operate wide to liberate spectrum for other uses, particularly in multiple frequency bands, but the lower bands (such as mobile broadband. That in turn has allowed policy-makers 700 and 800 megahertz, or MHz) can be more cost-effective, worldwide to institute spectrum refarming. In the United allowing for both wider coverage from fewer radio base States, the 700 MHz band, where LTE networks are stations (an important consideration for rural area deploy- currently being deployed, was released as a result of the ments) and higher powers to support building penetration digital switchover. Similarly, in Europe, countries such as (an important consideration in urban areas). Using optimal Sweden and Germany have taken advantage of the digital frequency bands can also assist with the high availability of switchover to release spectrum in the 800 MHz band for network equipment and lower prices resulting from global their LTE networks. economies of scale. Continuing with the previous example, deployments of LTE networks driven by U.S. and European Eliminate technological or service restrictions on spectrum. operators have generally been more successful in the 700 and The availability of spectrum is not the only issue. Technical 800 MHz bands. That has resulted in more affordable or technological restrictions or mandated uses that require network equipment in these two bands. the spectrum to be used for other services could still act as a Third, blocks of spectrum must be sufficiently large to bar to mobile broadband technologies. Eliminating such allow cost-efficient provision of mobile broadband, with restrictions, and making spectrum technologically neutral, multiple operators. LTE, for example, allows operations with allows operators to choose the most efficient technology to different-sized blocks of spectrum (from 1.4 to 20 MHz); the deploy on broadband services. Market mechanisms for spec- size of the spectrum blocks and the pairing of frequencies trum allocation, such as auctions or secondary trading, determines the maximum broadband speed and the cost of should help to ensure that available spectrum is used effi- deploying mobile broadband networks based on this tech- ciently. This is valid not only for current mobile broadband nology. Because data traffic and bandwidth are growing technologies, such as WiMAX, HSPA, or LTE, but also for rapidly, operators may need larger blocks of spectrum to other technologies that may be developed in the future. cope with demand and avoid congestion, particularly in Applying the principle of technological neutrality is as rele- urban areas. Use of Wi-Fi networks to offload mobile broad- vant for new spectrum being released as for spectrum that band traffic from cellular networks can also help to offset has already been allocated, particularly second- and third- congestion pressures over these networks. However, these generation (2G, 3G) band spectrum. Operators can thus complementary networks will not be able to solve the grow- leverage existing network deployments in the 2G- and ing congestion problem by themselves. Although forecast to 3G-bands, such as GSM (Global System for Mobile commu- almost double, Wi-Fi offload traffic is expected to handle nications), and Wideband CDMA (Code Division Multiple only around 20 percent of total mobile broadband data by Access), by turning over part or all of the spectrum they 2016 (CISCO 2012). already use for these services to advanced mobile broadband To minimize bottlenecks in the availability of spectrum, technologies (in-band migration). policy-makers and regulators should assess spectrum needs This practice has been successfully applied for 3G tech- and available cost-efficient technologies and release to the nologies within the 2G bands in many countries, particularly Policies for Mobile Broadband 105 in Latin America where operators could launch 3G services 26 times in five years (figure 7.3; CISCO 2012). The expan- before 3G licenses where awarded or in bands initially sion of data-hungry devices, such as smartphones and awarded for 2G services. In Mexico operators launched 3G tablets, are already resulting in exponential increases of services in 2007 and 2008 using both CDMA and Universal traffic in some countries (see figure 1.5). Mobile Telecommunications System (UMTS) technologies, Unlike fixed broadband technologies that can make use well before 3G spectrum licenses were awarded in 2009. In of the almost unlimited capacity of fiber optics to cope with Brazil operators started launching CDMA-3G services in growing data traffic, mobile broadband networks must 2004, before 3G licenses were awarded. In addition, the regu- work with finite allocations of spectrum. Mobile operators lator allowed the use of 2G-awarded spectrum for 3G ser- rely on optimization of networks and traffic management vices as 3G spectrum licenses were awarded in 2007.2 to increase efficiency, at least in the short term.4 However, Allowing the use of existing spectrum for any technology- operators may also use optimization and traffic manage- neutral use (given that these technologies do not result in ment techniques to hinder competition through data caps harmful interferences) also enables operators to follow a and by blocking or “throttling� access to applications. For phased and scalable approach to transition from 2G/3G instance, mobile network operators may limit the band- technologies to 4G technologies (such as LTE). width available to those applications that threaten to deprive them of revenue, such as Skype used as a substitute Focus on expansion of network coverage rather than on for voice calls. To avoid such practices, regulators have been spectrum proceeds. High up-front spectrum costs may limit imposing limits on traffic prioritization while permitting the capital available for operators to invest in coverage optimization of mobile broadband networks, within the beyond the most affluent areas (EC 2002; Delian 2001; Bauer network neutrality concept. 2002). There are several methods for awarding spectrum Network neutrality generally refers to the notion that an rights, the most common ones being auctions, beauty Internet Service Provider (ISP) should treat all traffic contests, and hybrid methods of these two. Although equally, including any content, application, or service auctions are generally considered more efficient than beauty (Atkinson and Weiser 2006). Based on this principle of contests, auction designs aimed at increasing up-front nondiscrimination, a growing number of jurisdictions have revenues for the government do not achieve the highest social adopted regulations that range from barring ISPs from welfare benefits (Hazlett and Munoz 2008, 2010). Indeed, managing internet traffic in a way that discriminates among auctions that extract high rents from operators may result in content providers to permitting “best efforts� to deliver delays of investments or in concentration of network cover- content on equal terms. These regulations have generally not age in urban and high-income areas, while rural and low- been applied to mobile networks, however. In some cases, income areas are not served (Patrick 2001). The results of the the justification for the exemption has been to allow mobile 3G auctions in Europe, where high proceeds were achieved, broadband networks to develop. Some governments are now but 3G network deployment was delayed for several years beginning to regulate certain practices, for example by and a number of licenses were returned, showed that high requiring full access to certain applications (such as Voice up-front costs may result in low or delayed investment over IP services, like Skype).5 It is also useful to promote (Gruber 2006). To encourage coverage in underserved transparency on the part of operators to explain how they areas, some governments, such as Chile (box 7.1), Germany are applying traffic management. (Brugger and Oliver 2010; Wireless Intelligence 2011), and Sweden,3 have introduced hybrid methods adding specific Limit spectrum hoarding that could distort competitive coverage obligations to mobile broadband spectrum conditions in the market. Making spectrum available to the licenses to cover underserved areas, or “white spots.� market is critical for developing mobile broadband, but this spectrum also must be used efficiently. Operators should use Require transparency in traffic management and safe- their spectrum allocations to provide services and not to guard competition. Demand for mobile broadband is distort the market or impede other providers from entering growing exponentially. Mobile data traffic, spurred by the market. To avoid these pernicious effects, governments mobile broadband growth, is expected to grow more than have introduced limitations in awarding spectrum, such as 106 Information and Communications for Development 2012 Box 7.1 Using reverse auctions to match spectrum allocations with coverage obligations in Chile In Chile, the government provided spectrum in multiple bands for mobile broadband in underserved rural areas. Chile offered subsidies through a reverse auction (resulting in a government subsidy of more than $100 million) to develop mobile broadband in around 1,500 municipalities in rural areas, where no broadband service was available. Extending coverage to these areas could mean that 90 percent of Chile’s population would have broad- band coverage. Minimum service conditions for broadband access (such as a 1 Mbit/sdown- link) and a ceiling on prices was established. The winner of the auction, Entel Movil, started deploying mobile broadband in these areas in September 2010.a The large expansion of mobile broadband services in the country, has permitted Entel Movil to achieve the largest share of mobile broadband connections in the country, surpassing its other two main competitors (figure 7.1.1). Box figure 7.1.1 Mobile broadband subscriptions per operator in Chile 800 600 Thousands 400 200 0 Se 9 Se 0 09 M 0 M -11 No 9 No 0 Ja 9 Ja 0 9 M 0 1 Ju 9 Ju 0 l-0 l-1 1 0 1 v-0 v-1 -0 -1 -1 -0 -1 n- n- p- p- n ar ar ar ay ay Ja M M Movistar Claro Entel Source: Subtel. a. Subsecretaria de Telecomunicaciones, Chile. 2010. Proyecto Bicentenario: “Red de Internet rural: Todo Chile comuni- cado.� http://www.subtel.gob.cl/prontus_subtel/site/artic/20100819/asocfile/20100819103226/ppt_bicentenario_fdt_red_internet _rural.pdf; Entel, Todo Chile Comunicado. http://personas.entelpcs.cl/PortalPersonas/appmanager/entelpcs/personas?_nfpb spectrum caps in specific bands (see above) or sunset clauses market needs and competitive conditions as they evolve. If in case the spectrum is not brought into timely use by a competition conditions are not in danger, regulators and certain date. However, governments should be wary of policy-makers would be better off monitoring market imposing spectrum caps that are too stringent and might conditions rather than establishing spectrum caps. Mobile impede operators’ ability to react to market demand. Broad- broadband demand can grow very quickly as more and more band data traffic demand is expected to require increasing applications are developed and handsets prices are reduced amounts of spectrum, especially in urban areas (Rysavy (see below). In this scenario, caps that are too stringent may Research 2010). For this reason, it is advisable for govern- result in underdevelopment of mobile broadband services, ments to be flexible in using spectrum caps and monitor the lower speeds, or limited quality of service. Policies for Mobile Broadband 107 Figure 7.3 Mobile data traffic by 2016, CISCO Foster infrastructure and spectrum sharing. Policies that forecast encourage infrastructure sharing allow operators to develop common networks, share costs, and hence lower investment 12 10.8 requirements, all of which can result in lower prices for 10 users.6 In Kenya, instead of auctioning LTE-band spectrum to separate operators, the government is planning to imple- 8 ment a PPP model with a sole network with LTE-band spec- Exabytes a month 6.9 trum available on an open-access basis. The possible risk is 6 that by creating an effective monopoly, deployment may be 4.2 4 slow and inefficient. On the other hand, by requiring 2.4 companies to share a common infrastructure, the aim is to 2 1.3 reduce duplicate investment and minimize competition 0.6 distortion (Msimang 2011). 0 11 12 13 14 15 16 20 20 20 20 20 20 Demand-side policies Source: CISCO 2012. Demand-side policies aim at expanding adoption of broad- Note: The compound annual growth rate between 2011 and 2016 is projected to be 78 percent. band services by addressing the barriers to adoption and fostering the development of broadband-based services and applications and thereby promoting user demand. As with Foster the development of national broadband backbone supply, local market conditions affect the effectiveness of networks. In contrast to voice mobile networks, mobile demand-side policies, and policy-makers and regulators broadband networks require high bandwidth backbones to should take good note of those conditions. Two main support the delivery of broadband to end users. To support barriers to entry are relatively common among developing rising volumes of mobile broadband traffic, the backbone countries, namely, the availability and affordability of networks of the mobile platform must be upgraded to fiber. broadband-enabled devices and service. In addition, the Governments can support the development of backbone development of services and applications that address local networks by enacting infrastructure sharing policies, allow- market needs has proven to be a critical driver of demand ing mobile operators to make rational build or lease deci- for broadband services, because such services can improve sions, streamlining procedures to obtain rights of ways (by their value proposition for businesses and consumers. issuing national rights of way, for example), and adopting other specific policies. In addition, governments can foster Ensure the availability and affordability of broadband- the development of backbone networks by coordinating enabled devices. As mobile broadband has expanded glob- with the private sector, providing seed capital for the devel- ally, the reach of broadband-enabled devices, such as opment of backbone networks, and enabling public-private handsets and tablets, has increased, and their price has fallen. partnership (PPP) schemes. However, governments must be As penetration continues in developing countries, manufac- careful to avoid market distortions when intervening in the turers are targeting these markets by providing low- and infrastructure market. ultra-low-cost devices and designs tailored to these markets’ In addition, governments can also encourage the open- needs. The global market for handsets has seen a continual ing to broadband operators of fiber infrastructure reduction in prices even as performance increases. Mobile deployed by other utilities, such as electricity, roads, or broadband handsets, or smartphones, have fallen in price water. Many utilities have already deployed fiber networks from more than $300 in 2005 to less than $100 in 2011 for for internal operational purposes, and their surplus low-end models (IBM 2011; Kalavakunta 2007). Devices capacity can be utilized for broadband development. costing under $16 are forecast by 2015 (Scottsdale 2011). Indeed, this surplus fiber capacity can serve to build or However, barriers such as taxes, import restrictions, and complement mobile broadband backbone networks duties may prevent consumers from benefiting from best (Arthur D. Little 2010). global market prices (Katz et al. 2011). Direct sales taxes 108 Information and Communications for Development 2012 affect all legitimate handsets on sale within a country, and A similar strategy is being applied to mobile broadband. their level should be assessed carefully by policy-makers to Operators provide prepaid packages and other tailored ser- avoid limiting broader access or spurring a profusion of vices for mobile broadband services, such as offering a USB “gray market� devices. Import restrictions and duties apply (universal serial bus) “dongle�10 with a certain amount of only to imported devices, but given that equipment manu- data that can be used on laptops or PCs over cellular facturing has become a global industry, virtually all devices networks. For instance, in the Arab Republic of Egypt are imported to some extent. The combination of sales taxes mobile operators are offering prepaid traffic-based mobile and import duties may increase prices to unaffordable levels broadband access starting at $8, less than 4 percent of the for most of the population. For instance, in Bangladesh monthly GNI per capita.11 In Colombia operators offer handsets are subject to a 12 percent import duty and an prepaid mobile broadband for different prices based on additional sales tax of 15 percent (Boakye et al 2010). duration and service access, ranging from $0.5 a day for chat Subsidization of handsets by the mobile voice industry or email access only to $25 a month for full broadband has made them affordable but has kept service prices high. access, less than 6 percent of monthly GNI per capita at the As a result, a few countries, such as Finland, have made the highest offering.12 Policy-makers and regulators should practice illegal.7 In the case of mobile broadband, though, enable these practices and avoid distorting the market high-end devices that make use of more efficient networks unnecessarily. Imposing a high level of taxes (particularly (such as LTE) may actually reduce unit prices for data. So, direct taxes) on mobile broadband service may reduce their policy-makers should be prepared to show evidence of affordability and deter adoption (Katz et al. 2011). market distortion effects before imposing bans on subsidiz- As the mobile voice market proved, competition among ing broadband-ready devices. service providers is also a critical driver of price reductions Finally, some countries have promoted domestic devel- and innovative offerings that increase affordability opment of cheap handsets. For instance, India has fostered (Rossotto et al. 1999). Policy-makers and regulators should the development of cheap tablets coupled with a program of safeguard competitive conditions in the market and, when subsidies for the education sector, making tablets for educa- needed, increase competition (by reducing barriers to entry tion available for $35, less than 3 percent of that country’s to the market, for example, or increasing the number of annual gross national income (GNI) per capita.8 Not all licenses). countries have the manufacturing base, low labor costs, and large domestic market size of India, however, so policy- Enable the development of broadband applications and makers need to evaluate carefully the potential for success of content. Applications and content are drivers of broadband these kinds of policies in their local markets. Without demand. Broadband in itself does not provide much value import protection, it is difficult to compete on cost and directly to business and consumers. It is the applications and quality with the global market. content that can be accessed through broadband that consumers want. Mobile broadband has made this link even Enable increasing affordability of broadband services. more evident. Adoption of mobile broadband services is Along with the cost of the handsets themselves, service costs closely followed by applications growth for this service may deter access to broadband. Mobile operators have (figure 7.4). generally been successful at reducing the total cost of Mobile applications are easier to use than earlier web- ownership for mobile phones, in best practice cases to based applications and allow additional features, such as below $5 a month for a basket of services.9 Prepaid offerings geo-location of services, unique to mobile services. Coupled have been the most successful marketing strategy to with social networks, applications are now the main demand increase the affordability of mobile services. In fact, prepaid drivers for mobile broadband. But most mobile broadband service has been an important driver of mobile telephony in applications and services are developed in and for developed developing countries; for example, more than 80 percent of countries. For instance, the vast majority of downloads for all users in Africa, Asia Pacific, and Latin America in the the Android platform have occurred in the United States, third quarter of 2011 bought prepaid service (Wireless followed by the Republic of Korea, Japan, and other devel- Intelligence 2011). oped countries (Empson 2011). Policies for Mobile Broadband 109 Figure 7.4 Mobile applications as a driver of mobile On the demand side, limited availability of affordable broadband demand broadband-enabled devices and services, as well as the lack of local applications and content, are the main bottlenecks and 35 19 20 18 market failures. The policy recommendations described in 30 31 16 this chapter provide guidance on how to address these 25 13 14 common barriers. Percentage 12 Billions 20 9 10 This report has shown the potential of mobile applica- 15 6 8 6 tions to transform different sectors of the economy while 10 4 10 5 4 benefiting the livelihoods and lifestyles of citizens and 2 0 0 0.2 3 0 communities. Mobile broadband is an important element in * that process, because it will offer the tools, from smart- 07 08 09 10 11 20 20 20 20 App downloads (billion) 20 Mobile broadband (per 100 people) phones to services, that enable that transformation to take Source: Adapted from Apple, Google, and Wireless Intelligence. place: from access to apps. Note: * Estimate. Notes 1. http://www.itu.int/ITU-D/ict/statistics/. To foster local demand for mobile broadband applica- 2. Telegeography Inc., Globalcomms database, 2012. tions and content, policy-makers actively promote local 3. Telecoms.com, 2010, “Sweden to Auction 800 MHz Spectrum in February� (December), http://www.telecoms.com/23770/ capacity for development and customization. Policy- sweden-to-auction-800mhz-spectrum-in-february-2011/; IT makers can develop policies to provide the right enabling World, 2010, “Spectrum for Rural 4G Auctioned Off in environment for this industry and to actively foster its Sweden� (March), http://www.itworld.com/mobile-amp-wire- development through the creation of a mobile broadband less/139121/spectrum-rural-4g-auctioned-sweden; Economist innovation ecosystem. Co-creation platforms linking Intelligence Unit, 2011, “Germany/Sweden Telecoms: Fixing educational institutions and industry as well as technol- Mobile Broadband� (June), http://viewswire.eiu.com/index .asp?layout=ib3Article&pubtypeid=1162462501&article_id= ogy hubs and crowdsourcing strategies are some of the 1838266568&rf=0. tools for creating such an ecosystem. In addition, policy- 4. Mobile network optimization and self-organizing networks makers can encourage government agencies to develop are expected to grow over 84 percent from 2010 to 2015 as mGovernment applications (see chapter 6) and content LTE networks are deployed worldwide. See TotalTelecom for mobile broadband (through open data policies, for (December 2011–January 2012), http://www.totaltele.com/. example), as well as acting as a consumer for sectoral 5. For instance, the United Sates has limited the application of applications (in education or health, for instance), in network neutrality principles to wireless operators. However, order to create a critical mass for the development of local the government prohibits operators from blocking certain applications and content. websites and applications. In France, network neutrality rules apply to all broadband operators (including wireless), although the regulator can still apply less stringent rules for Conclusions traffic management for mobile operators based on objective reasons. In the Netherlands the Parliament passed a law Fostering mobile broadband diffusion in developing coun- forbidding mobile operators from blocking applications, tries requires appropriate policy actions to enable and particularly VoIP and text messaging. See http://www.iptele- encourage both components of the mobile broadband phonyusa.net/internet-protocol/2846-dutch-pass-law-to- ensure-open-internet-access. ecosystem—supply and demand. Policy-makers should eval- 6. Telecoms.com, 2009, “Tele2, Telenor to Build Swedish LTE uate local conditions before applying specific policies, screen- Network� (April), http://www.telecoms.com/10423/tele2- ing for bottlenecks or market failures on each of side of the telenor-to-build-swedish-lte-network/; Telegeography, 2011, ecosystem. The most common bottlenecks and market fail- “Telia and Telenor Share Danish Networks� (June), http:// ures on the supply side are spectrum and backbone networks. www.telegeography.com/products/commsupdate/articles/ 110 Information and Communications for Development 2012 2011/06/14/telia-and-telenor-share-danish-networks/; CISCO. 2012. “CISCO Visual Networking Index: Global Mobile Unwired Insight, 2010, “LTE Leader TeliaSonera Launches 4G Data, Traffic Forecast Update 2011–2016.� http://www in Denmark� (December), http://www.unwiredinsight.com/ .cisco.com/en/US/solutions/collateral/ns341/ns525/ns537/ns705/ teliasonera-4g. ns827/white_paper_c11-520862.pdf. 7. “Market Analysis of Mobile Handset Subsidies,� http://www Delian, A. 2001. “3G Mobile Licensing Policy: From GSM to IMT- .netlab.tkk.fi/tutkimus/lead/leaddocs/Daoud_Haemmaeinen 2000, a Comparative Analysis.� http://www.itu.int/osg/spu/ni/ _slides.pdf. 3G/casestudies/GSM-FINAL.pdf. 8. “India’s Aakasha Tablet Soon to Be Free for Students� (Febru- Digits. 2011. “The Facebook App Economy.� Center for Digital Inno- ary 2012), http://androidcommunity.com/indias-aakash- vation Technology and Strategy, University of Maryland tablet-soon-to-be-free-for-students-20120208/. (September 19). http://www.rhsmith.umd.edu/digits/pdfs_docs/ 9. Nokia and LIRNEasia conduct an annual survey of the total research/2011/AppEconomyImpact091911.pdf. cost of ownership (TCO) of mobile, covering user prices for The Economist. 2011. “Apps on Tap.� http://www.economist.com/ voice, SMS and data, a SIM card, taxes, and local handset node/21530920. costs in 50 countries. In the June 2011 study, Sri Lanka came EC (European Commission). 2002. “Comparative Assessment of the out the cheapest, at $2.91 a month; 10 other countries had a Licensing Regimes for 3G Mobile Communications in the Euro- TCO under $5 a month, excluding data. By contrast, in pean Union and Their Impact on the Mobile Communications Morocco the same basket of services provided in Sri Lanka Sector,� http://ec.europa.eu/information_society/topics/telecoms/ would cost $52.14; see: http://lirneasia.net/2011/06/nokia- radiospec/doc/pdf/mobiles/mckinsey_study/final_report.pdf. annual-tco-total-cost-of-ownership-results-show-bangladesh- Empson, R. 2011. “Android Global: South Korea Second Only to and-sri-lanka-as-cheapest/. US in App Downloads.� http://techcrunch.com/2011/11/16/ 10. A “dongle� or data card is a piece of hardware that plugs into android-global-south-korea-second-only-to-u-s-in-app- a PC, tablet, or other computing device to permit it to use downloads/. mobile data services. Similar to Wi-Fi cards that proliferated Friedrich, R., K. Sabbagh, B. El-Darwiche, and M. Singh. 2009. in the early 2000s, the market for such devices is likely to “Digital Highways: The Role of Government in 21st Century disappear once the hardware is increasingly built into the Infrastructure.� Booz & Company. http://www.booz.com/media/ device itself. uploads/Digital_Highways_Role_of_Government.pdf. 11. See Vodafone Egypt’s offering: http://www.vodafone.com.eg/ Gruber, H. 2006. “3G Mobile Telecommunications Licenses in vodafoneportalWeb/en/P604978041288690285509. Europe: A Critical Review� (November). http://papers.ssrn 12. See Movistar’s prepaid offering: http://www.movistar.co/ .com/sol3/papers.cfm?abstract_id=918003&download=yes. Personas/Internet_Movil/Planes/Internet_prepago/internet Hazlett, T., and R. Munoz. 2008. “A Welfare Analysis of Spectrum _para_telefonos/. Allocation Policies� (December). http://mason.gmu.edu/ ~thazlett/pubs/Hazlett.Munoz.RandJournalofEconomics.pdf. ———. 2010. “What Really Matters in Spectrum Allocation References Design� (April). http://businessinnovation.berkeley.edu/ Arthur D. Little. 2010. “FTTH: Double Squeeze of Incumbents— Mobile_Impact/Hazlett-Munoz_Spectrum_Matters.pdf. Forced to Partner?� http://www.adl.com/uploads/tx_ IBM. 2011. “Telco 2015: Five Telling Years, for Future Scenarios.� extthoughtleadership/ADL_Double_Squeeze.pdf. http://www.ieee-iscc.org/2010/keynoteSlides/Franco%20 Atkinson, R., and P. Weiser. 2006. “A ‘Third Way’ on Network Prampolini.pdf. Neutrality.� Information Technology and Innovation Founda- ITU (International Telecommunication Union). World Telecom- tion (May 30). http://www.itif.org/files/netneutrality.pdf. munication/ICT Indicators Database. www.itu.int/ti. Bauer, J. 2002. “Spectrum Auctions: Pricing and Network Expan- Kalavakunta, R. 2007. “Low Cost Mobile Broadband Access.� sion in Wireless Telecommunications.� http://arxiv.org/ftp/cs/ http://www.itu.int/ITU-D/afr/events/PPPF/PPPF-Africa2007/ papers/0109/0109108.pdf. documents/presentations/Session2/Low_Cost_BWA_06_04_ Boakye, K., et al. 2010. “Mobiles for Development.� http://www 2007.pdf. .mobileactive.org/files/file_uploads/UNICEF%20Mobiles4Dev Katz, R., et al. 2011. “The Impact of Taxation on the Development %20Report.pdf. of the Mobile Broadband Sector.� GSM Association. http:// Brugger, R., and K. Oliver. 2010. “800 MHz Auctions and Imple- www.gsma.com/documents/the-impact-of-taxation-on-the- mentation of the DD in Germany� (October). http://tech.ebu development-of-the-mobile-broadband-sector/19669. .ch/docs/events/ecs10/presentations/ebu_ecs10_workshop_ Katz, R., S. Vaterlaus, P. Zenhäusern, and S. Suter. 2010. “The Impact brugger_kluth.pdf. of Broadband on Jobs and the German Economy.� Intereconomics: Policies for Mobile Broadband 111 Review of European Economic Policy 45 (1, January). http:// Rossotto, C., et al. 1999. “Competition in Mobile Telecoms� (April). www.polynomics.ch/dokumente/Polynomics_Broadband_ http://www-wds.worldbank.org/servlet/WDSContentServer/ Brochure_E.pdf. WDSP/IB/1999/09/14/000094946_99072807530926/Rendered/ Kelly, T., and C. Rossotto. 2011. Broadband Strategies Handbook. PDF/multi_page.pdf. infoDev and World Bank. www.infodev.org/en/Document Rysavy Research. 2010. “Mobile Broadband Capacity Constraints .1118.pdf. and the Need for Optimization� (February). http://rysavy.com/ Msimang, M. 2011. “Broadband in Kenya: Build It and They Will Articles/2010_02_Rysavy_Mobile_Broadband_Capacity_ Come.� infoDev. http://www.infodev.org/en/Publication.1108 Constraints.pdf. .html. Scottsdale, A. 2011. “Pent-Up Demand and Falling Price Drive Patrick, X. 2001. “Licensing of Third Generation (3g) Mobile: Strong Entry-Level Market Growth.� http://www.abiresearch Briefing Paper.� http://www.itu.int/osg/spu/ni/3G/workshop/ .com/press/3573-Pentup+Demand+and+Falling+Prices+ Briefing_paper.PDF. Drive+Strong+Entry-Level+Handset+Market+Growth. Qiang, C., and C. Rossotto. 2009. “IC4D: Extending Reach and Thomson, H., et al. 2011. “Economic Impacts of Mobile versus Increasing Impact.� Economic Impacts of Broadband, ch. 3. Fixed Broadband.� Telecommunications Policy. http://www Washington, DC: World Bank. .sciencedirect.com/science/article/pii/S0308596111001339. Qiang, C., and L. Xu. Forthcoming. “Telecommunications and Wireless Intelligence. 2011. “Germany Rolls Out LTE to Rural Economic Performance: Macro and Micro Evidence.� Areas.� https://www.wirelessintelligence.com/analysis/2011/ World Bank, Washington, DC. 06/germany-rolls-out-lte-to-rural-areas/. 112 Information and Communications for Development 2012 Part II: Statistical Appendix Key Trends in the Development of the Mobile Sector Michael Minges Access of lower on-network calling prices or to separate business from personal calls), and thus have multiple subscriptions. Measuring mobile take-up In the United Arab Emirates in 2010, for example, 28 percent Mobile telephony has been one of the most quickly of subscriptions were duplicates, mainly for these reasons, as adopted technologies of all time. While 128 years passed well as for roaming and gaining better coverage in different before fixed telephone lines reached 1 billion users, mobile parts of the country (UAE 2011). networks achieved this milestone in just over two decades Another factor skewing the figures in some countries is the (figure A.1). Even more astounding, mobile networks have number of mobile cellular subscriptions taken by people resid- roughly doubled in size every two years since 2002. By the ing in bordering nations. Subscriptions can also be inactive, end of 2011, there were 5.9 billion mobile cellular subscrip- with the length of time that must pass before the subscription tions worldwide. elapses varying by operator. At the same time, an increasing This huge growth in mobile subscriptions has led to a number of devices are connected to mobile networks that do significant increase in penetration. The traditional measure not use voice services or do not interface with humans. These of mobile telephony penetration is the number of subscrip- include laptop computers, as well as equipment such as auto- tions per 100 people. By the end of 2011, more than 8 of mated teller machines. In Spain, these types of subscriptions every 10 people around the world had a mobile subscrip- accounted for 10 percent of the mobile market in 2010. tion, up from just over 1 in 10 in 2000, with particularly Although methods other than counting subscriptions strong gains in middle-income countries (figure A.2). Over may be more precise for measuring access to mobile phones, the span of a single decade, mobile telephones have changed subscription data are most widely available. For example, from an elitist gadget that was mainly the preserve of high- another useful measure could be the number of persons income countries to a mass-market tool spanning the globe. with access to a mobile phone. But gathering that data Some 90 economies—almost half of the member coun- requires the use of surveys, which are conducted only infre- tries of the World Bank—had a mobile penetration exceed- quently or, in many countries, not conducted at all. ing 100 percent in 2011. Because there are more mobile Another measure is the number of households where at subscriptions than inhabitants in these countries, these least one household member has a mobile phone. This statistics do not reflect the number of people who actually metric is useful because it is precise: it cannot exceed 100. have use of a mobile phone, because the same person may If a mobile phone exists in a household, then all members possess multiple SIM cards (for example, to avail themselves 115 Figure A.1 Worldwide fixed and mobile telephone subscriptions 10 The number of mobile subscriptions 9 will soon overtake the world's population 8 7 6 1978: First commercial Billions 5 1876: cellular mobile First two-way services 4 telephone established conversation 2002: 3 There are over 1 billion mobile subscriptions, 2 passing fixed-line users 1961: 1 85 years later, fixed-line subscriptions reach 100 million 0 18 6 18 2 18 8 19 4 11 0 19 1 00 19 6 19 2 19 8 24 19 0 19 6 19 2 19 8 19 4 19 0 19 6 19 2 19 8 19 4 19 1 96 20 2 08 14 7 8 8 9 0 1 1 3 3 4 4 5 6 6 7 7 8 8 9 9 0 18 19 19 20 20 Fixed lines (bn) Mobile subscriptions (bn) World Population (bn) Source: Adapted from ITU, World Bank estimates. Note: Log scale. Figure A.2 Mobile cellular subscriptions per 100 Nations recommended in 2008 that the question “House- people, by income group hold having mobile cellular telephone(s)� be included in the questionnaires used for the 2010 round of censuses.1 140 Based on the surveys carried out by a significant number of countries, almost three of four households were esti- Number of subscriptions per 100 people 120 118 High 116 mated to have mobile phone service in 2010. 100 Another factor to consider is household size. Individual 85 use surveys tend to exaggerate subscription penetration 80 78 WORLD rates in developed economies, while household surveys 60 Upper-middle suggest that the level of access to mobile is higher in many 50 40 Lower-middle 38 developing countries than subscription penetration figures would suggest. Access is particularly high in coun- 20 12 Low tries with large households. Take Senegal, where the 11 0 3 subscription penetration was 57 per 100 people in 2009, 0.3 but household penetration was estimated to be 30 points 01 02 03 04 05 06 07 08 09 10 11 20 20 20 20 20 20 20 20 20 20 20 higher at 87 (figure A.3a). This larger household size can Source: Adapted from ITU, and author’s own estimates. dramatically extend access to mobile phones, considering that on average nine persons are in each Senegalese house- hold. Several low-income nations have higher mobile could theoretically use it, thereby extending access. House- phone home penetration than some developed economies. hold availability has thus been the traditional indicator for For example, Senegal, along with some other low- and measuring universal service. This indicator is collected by middle-income economies, has a higher proportion of a growing number of countries through ongoing house- homes with mobile phones than either Canada or the hold surveys, as well as special health surveys. The United United States (figure A.3b). 116 Information and Communications for Development 2012 Figure A.3 Mobile household penetration, Senegal and other selected countries, 2009 a. Mobile penetration, Senegal, 2009 b. Homes with a mobile phone, %, 2009 100 Maldives 97.3 90 80 Jordan 97.1 70 Samoa 94.0 60 Senegal 85.8 50 40 Paraguay 85.6 30 United States 82.7 20 10 Honduras 79.6 0 Canada 77.2 Mobile subscriptions per Percent of households 100 people with a mobile subscription Source: Adapted from Autorité de Régulation des Télécommunications et des Posts (Senegal) and national household and health surveys. Reaching the base of the pyramid middle-income economies, estimated to be 1.1 billion, At the turn of the new millennium, most analysts would might be considered outside the target market.3 That have considered a world with 6 billion cellular phones leaves an addressable unserved population of just 300 impossible. At the time, there were some 700 million mobile million people worldwide at the start of 2012. subscriptions, 70 percent of which were located in high- Mobile equipment manufacturer Nokia has calculated a income economies. This link between mobile penetration total cost of ownership (TCO) measure that factors in the and national income gave rise to a belief that there was a cost of the handset, service charges, and taxes (Nokia 2009). price below which mobile service would be unprofitable, The TCO needs to be adjusted by income, given that levels of thereby making it commercially unviable and unaffordable income vary between countries. Even if users can afford for many in lower-income countries. After all, fixed tele- service, they still need signal coverage. Figure A.5 illustrates phones had been in existence for more than a century, yet affordability and coverage for selected developing countries. penetration rates were still less than 1 in 100 in many devel- The relationship lends itself to four scenarios bounded by oping nations. affordability of 10 percent (that is, where mobile services are The mobile industry has defied that theory. Every year, it either less or more than 10 percent of income) and coverage expands its user base, reaching more and more low-income (where mobile covers either less or more than 9 percent of users. This has been made possible by cheaper equipment, the population). These scenarios are reflected in the four falling handset prices, prepaid subscriptions, flexible quadrants in figure A.5: regulation, competition for marginal users as markets 1. high affordability and high coverage (upper left quad- become saturated at the top, and rising incomes.2 A recent rant) study carried out in three provinces in China found that 95 percent of rural households had a mobile tele- 2. high affordability and low coverage (lower left quad- phone (box A.1). Nonetheless, a significant proportion of rant) the world’s population has no mobile connection. Of the 3. low affordability but high coverage (upper right quad- some 5.9 billion mobile subscriptions in the world, rant) 3.4 billion were in low- and middle-income economies (figure A.4). Given some 4.8 billion residing in those 4. low affordability and low coverage (lower right quadrant) countries, that leaves a gap of 1.4 billion without a Countries where mobile services cost less than 10 percent mobile subscription. The number of people living on less of income and cover at least 90 percent of the population than $1.25 a day (purchasing power parity) in low- and Key Trends in the Development of the Mobile Sector 117 Box A.1 Mobile use in rural China An ongoing World Bank project has been investigating attitudes, use, and impact of informa- tion and communication technologies in rural China. Funded by the Bill and Melinda Gates Foundation, one of the activities was a survey in rural areas of three provinces (Jilin, Guizhou, and Shandong). Some 58 percent of the population in these provinces is rural; the combined rural population is 88 million, which would make the three provinces the 13th largest country in the world (about the size of Vietnam). The survey, carried out in October 2011, found very high use of mobiles, with 95 percent of rural households reporting having one. Individual ownership was lower at 85 percent, but over half of individuals without their own mobile reported they did not have one because they could use someone else’s or they had no need. Around half of mobile phone owners reported sending text messages, and some 13 percent use the internet from their cell phone. One interesting finding was the relatively large amount spent on mobile services. Average monthly mobile phone service expenditure was 13 percent of income, with users willing to devote up to 18 percent of their income to mobile services. Box Figure A.1.1 Mobile usage in rural areas of three Chinese provinces, 2011 a. Does your household have a mobile phone? b. Why don’t you have your own mobile phone? Other 6% No 5% Don’t know how to use No need 14% 31% Handset too expensive % siv e 13% 14 pen arg e Can use ex e ch Yes another phone too rvic 22% Se 95% c. Do you use the mobile phone for: d. Amount spent for mobile service as % of income: 20 18 Accessing Internet 13.8 18 16 Sending SMS 50.7 14 13 12 Receiving SMS 54.8 10 8 6 Making calls 98.1 4 2 Receiving calls 99.1 0 Actual amount Amount willing to spend % of respondents Source: World Bank. tend to have high levels of access (measured by the availabil- operators have worked in the country for more than a ity of mobile phones in households). decade, they used different technologies, which drove up Service charges alone do not explain the problem. equipment costs and made it difficult for subscribers to Consider Angola, which has relatively low tariffs but also switch from one operator to the other. A mobile technol- low coverage. Mainly because of lack of competition, ogy (GSM) common to both operators has been available Angola has not been successful in expanding mobile only since November 2010. Further, the market remains a coverage compared with peer countries. While two duopoly. 118 Information and Communications for Development 2012 Figure A.4 Population, mobile subscriptions, and Densely populated and relatively small, Malawi has been rela- poverty headcount in low- and middle- tively easy to cover. Attempts to introduce additional compe- income economies tition have not been completely successful, however, and the market remains dominated by two operators. The least desir- Low & middle income economies (people, billions) 6.0 able position is to have high tariffs and low coverage. In 4.8 Madagascar, the Nokia TCO amounts to over one-third of 5.0 4.0 3.4 income, and only around three-fifths of the population is Billions 3.0 covered. Although there are three operators, competition has 2.0 1.4 been affected by high interconnection charges. 1.1 1.0 In contrast, some countries have a high degree of afford- - ability and coverage but relatively low take-up. The Arab Population Mobile No mobile Poverty subscriptions subscription headcount Republic of Egypt has a high penetration of fixed telephone ratio at $1.25 lines that provide an alternative to mobile. In Bangladesh a day (PPP) mobile calls cost about one U.S. cent a minute, and, accord- Sources: ITU and World Bank data and World Bank estimates. ing to Nokia, its mobile tariffs are among the lowest in the Note: PPP = purchasing power parity. world.4 Coverage is high at 99 percent of the population. Despite these extremely low prices and very high coverage, Figure A.5 Affordability and coverage in developing household penetration stood at around 64 percent in 2010. economies According to mobile operator Grameenphone, its attempts to expand access are difficult because of the high SIM tax, Egypt, Arab. Rep. which has remained “the biggest barrier to the growth of Mobile coverage (% of population), 2010 Malawi mobile telephone industry in Bangladesh� (Grameenphone Bangladesh 2011). The tax of Tk 800 ($11.60) on new SIM cards has a 90 huge negative impact on low-end subscribers. If the SIM tax were eliminated, an estimated 90 percent of Bangladeshi households could afford mobile service. The GSM Associa- tion has called on the Bangladesh government to end the Madagascar SIM tax, citing it as the “single largest obstacle to the acqui- Angola sition of new subscribers.� (GSMA 2009) Operators are looking at innovative ways to widen access, 50 including lowering recharge values, conducting more 1 10 100 consumer research among bottom-of-the-pyramid popula- TCO as percent of GNI per capita (US$), 2010 tions, and developing low or alternative energy base stations. Mobile penetration (% of households) Another possibility is through virtual telephony using < 80% 80–90% > 90% emerging cloud networks. Users would not need to buy a Sources: Adapted from Nokia (2009), ITU and World Bank estimates. handset and would instead be allocated a number that they Note: Horizontal scale is logarithmic. TCO is “total cost of ownership,� reflecting the average costs, by country, of handset purchase, service can use on a borrowed phone. Their contacts and voice mail charges, and taxes. GNI is gross national income per capita. The ratio of would be stored on the cloud, where there would also be a TCO to GNI per capita is therefore an approximate measure of affordability gateway to mobile money services. Virtual telephony also per capita. lowers the cost of acquiring new users; for example, a trial network in Madagascar claims it costs operators just $0.20 to At the same time, other countries have relatively high establish cloud-based virtual telephony services, compared coverage along with relatively high prices. Consider Malawi, with $14–$21 to deliver a SIM card.5 where mobile networks are estimated to cover more than The barriers to increasing access to mobile communica- 90 percent of the population but where the Nokia annual tions for every household in the world are more of a regulatory TCO amounts to more than half of per capita income. and policy nature rather than technical. Introducing and Key Trends in the Development of the Mobile Sector 119 strengthening competition and eliminating special “mobile� A number of these subscriptions are not active users of taxes could significantly narrow the range of those not served mobile broadband (that is, they do not use the internet at by mobile communications. The remaining few households mobile broadband speeds, even though they are equipped to without access could then be captured through universal access do so). Users could have a theoretical ability to use mobile programs. It is also important to ensure that those at the broadband by having coverage and a mobile-broadband- bottom of the pyramid also enjoy access to value-added serv- enabled device, but they may not necessarily be using high- ices, which requires capacity building to understand how these speed services, perhaps because of high prices. They could services can benefit their lives and how to use them. also be subscribing to mobile broadband and using a high- speed mobile service (such as video telephony), but not necessarily accessing the internet. Alternatively, they could Mobile broadband be using mobile broadband to access the internet over hand- Using the ITU/OECD definition of broadband—networks sets, as well as through laptops or tablets. with a minimum download speed of 256 kilobits per second This definitional challenge presents analytical difficulties (kbit/s)—the first mobile broadband networks were launched with interpreting mobile broadband statistics. The issue is in late 2000 in Japan (W-CDMA) and in 2001 in the Repub- whether to count and include theoretical access, active access lic of Korea (EV-DO). According to industry sources, there to any high-speed service, active access using internet were 939 million mobile broadband subscriptions worldwide browsers, or active access via data cards (figure A.6b). Inter- in June 2011 (figure A.6a). This number implies that just over governmental agencies have called for more clarity on mobile 15 percent of the global subscription base can theoretically broadband statistics (OECD 2010). However, most countries use mobile network services at high speeds. report their mobile broadband statistics in insufficient detail, Figure A.6 Mobile broadband a. Estimated mobile broadband subscriptions, June 2011 b. Definitional “layers� of mobile broadband Mobile subscriptions Subscriptions capable of EVDO 20% mobile broadband Subscriptions using mobile broadband for video calling and other data but not necessarily Internet 939 Million Subscriptions using mobile broadband to W-CDMA/ access Internet HSPA 80% Subscriptions using data cards to access Internet Source: Adapted from CDMA Development Group and Global Mobile Suppliers Association (figure A.6a). Note: Not including LTE (estimated at 2 million subscriptions) or WiMAX (estimated at 20 million). 120 Information and Communications for Development 2012 so data comparability remains limited. Given these defini- world accessed the internet from their mobiles in 2010, up tional issues, some countries have gone with the lowest from some 180 million in 2005. Developing countries in Asia common denominator, counting only internet access account for over half of this total, with some two out of five through data cards as mobile broadband (denoted by the mobile internet users in China alone. innermost circle in figure A.6b). In addition to the statistical challenge of measuring active Despite confusion over statistical definitions, mobile mobile broadband users, there are often significant shortfalls broadband is already concretely impacting a number of between the theoretical and actual speeds of data through- developing countries, allowing them to leapfrog a lack of put. Manufacturers and operators cite ever-increasing band- fixed broadband infrastructure. Based on the more certain width, but the average speeds fall far short. According to yardstick of data cards (arguably the most direct comparison Akamai’s analysis of 96 mobile networks across 58 economies with wired broadband subscriptions), then mobile broad- carried out in the third quarter of 2011, peak speeds were band far surpasses fixed broadband in nations such as the around 8.9 megabits per second (Mbit/s), but average speeds Philippines and South Africa (figure A.7). And if the wider were 1.8 Mbit/s (Akamai 2012). In contrast, Akamai reported definition for mobile broadband of plain internet access is average download speeds of 4.7 Mbit/s for fixed broadband applied, then the combination of wireless networks such as networks. Further, usage over mobile broadband networks is GPRS, EDGE, CDMA2000 1x, mobile broadband, and generally “capped�; if users exceed a preset amount of data WiMAX greatly exceeds wired connections in most develop- transfer, then they no longer have access to data services or ing countries. An estimated 750 million people around the their speed may be reduced or they will have to pay overage charges. Mobile data usage varies tremendously around the world. In the third quarter of 2011 it averaged 536 Figure A.7 Broadband subscriptions in the megabytes (MBs) per month across networks in 58 coun- Philippines and South Africa tries with a low of 22 MB per month and a high of 4,906 MB Philippines per month (table A.1). 3,500 3,190 While high-speed wireless holds promise for reducing the 3,000 broadband divide, countries need to allocate spectrum and 2,500 2,197 license operators to provide services. At the end of 2011, 46 Thousands 2,000 1,554 World Bank members—almost all developing countries— 1,500 had not commercially deployed mobile broadband services. 1,000 632 1,149 And in a number of developing countries, a high-speed 328 776 898 500 22 122 433 wireless service may technically exist, but it is often available 0 111 185 384 only as a fixed wireless option. 05 06 07 08 09 10 11 20 20 20 20 20 20 20 South Africa Devices 3,000 2,500 2,500 According to Gartner, global sales of personal computers 1,953 2,000 (PCs) numbered 353 million in 2011.6 Assuming a PC is Thousands 1,419 1,500 replaced on average every five years,7 an estimated total of 1,000 811 1.6 billion PCs were in use around the world at the end of 500 380 625 725 818 2011. In comparison, some 1.8 billion mobile handsets were 115 520 374 0 223 sold in 2011 alone (figure A.8a).8 In other words, more mobile phones were sold in 2011 than the entire base of 06 07 08 09 10 11 20 20 20 20 20 20 installed PCs. Sales of smartphones rose 59 percent in 2011 Fixed Wireless to more than 470 million units, about one of every four Sources: Adapted from Globe Telecom, PLDT, MTN, Telkom, and Voda- mobile handsets. com. Note: “Wireless� refers to data cards only and not to access directly from Another entry into the device world came in April handsets. Data are for major operators only. Figures for South Africa have 2010. The Apple iPad, which straddles the boundary Key Trends in the Development of the Mobile Sector 121 Table A.1 Mobile data speeds and volumes, Q3 2011 Average speed Average data usage Economy Network (kbit/s) Peak kbit/s (MB/month) Australia AU-3 1,553 7,878 222 Austria AT-1 2,903 10,722 142 Belgium BE-2 1,938 5,277 22 Bulgaria BG-1 1,715 7,499 127 Canada CA-2 1,171 2,923 608 Chile CL-3 1,560 11,207 133 China CN-1 1,475 3,927 247 Colombia CO-1 1,003 6,541 156 Czech Republic CZ-1 1,709 8,630 87 Egypt, Arab Rep. EG-1 575 3,344 155 El Salvador SV-3 926 4,782 353 Estonia EE-1 1,401 7,487 264 France FR-2 2,382 8,542 1,714 Germany DE-1 967 3,720 93 Greece GR-2 1,199 4,179 132 Guam GU-1 957 4,663 101 Guatemala GT-1 1,441 7,379 411 Hong Kong SAR, China HK-2 1,925 10,842 583 Hungary HU-1 1,863 8,481 130 India IN-1 1,597 9,443 274 Indonesia ID-1 475 7,172 4,906 Ireland IE-1 2,880 14,055 725 Israel IL-1 1,435 6,419 69 Italy IT-4 1,413 8,693 219 Kuwait KW-1 1,444 6,979 252 Lithuania LT-2 1,973 11,945 414 Malaysia MY-3 1,024 7,598 361 Mexico MX-1 1,233 6,938 94 Moldova MD-1 1,791 7,183 142 Morocco MA-1 1,256 10,925 322 Netherlands NL-1 1,763 4,871 36 New Caledonia NC-1 1,070 4,757 854 New Zealand NZ-2 1,880 9,988 768 Nicaragua NI-1 1,551 7,886 754 Nigeria NG-1 254 5,024 514 Norway NO-2 2,071 6,752 58 Pakistan PK-1 691 4,682 332 Paraguay PY-1 643 5,850 163 Poland PL-2 1,511 7,593 78 Portugal PT-1 880 4,277 200 Puerto Rico PR-1 2,639 10,975 2,703 Qatar QA-1 1,620 10,074 281 Romania RO-1 884 4,250 91 Russian Federation RU-3 995 3,990 117 Saudi Arabia SA-1 1,672 8,713 357 Singapore SG-4 1,585 9,490 289 Slovakia SK-1 327 2,077 38 Slovenia SI-1 2,189 8,687 54 South Africa ZA-1 438 1,386 168 Spain ES-2 1,089 8,648 149 (continued next page) 122 Information and Communications for Development 2012 Table A.1 continued Average speed Average data usage Economy Network (kbit/s) Peak kbit/s (MB/month) Sri Lanka LK-1 894 7,373 327 Thailand TH-1 149 1,412 135 Turkey TR-1 1,771 7,975 203 Ukraine UA-1 2,227 7,500 128 United Kingdom UK-3 4,009 19,334 81 United States US-2 1,072 4,411 47 Uruguay UY-2 542 4,712 63 Venezuela, RB VE-1 911 6,146 178 AVERAGE 1,818 8,960 536 Source: Akamai 2012. Figure A.8 Global sales of mobile and computing devices a. Mobile handsets b. PCs, smartphones, and tablets 2,000 30 1,000 1,800 900 25 1,600 800 1,400 700 20 1,200 600 Percentage Millions Millions 1,000 15 500 800 400 10 600 300 400 200 5 200 100 0 0 0 05 06 07 08 09 10 11 05 06 07 08 09 10 11 20 20 20 20 20 20 20 20 20 20 20 20 20 20 Year Year Mobile handset sales Smartphone % Tablets Smartphones PCs Source: Adapted from Gartner Inc. Note: In these figures, PC includes desk-based and mobile PCs, including mini-notebooks, but not tablets. between smartphones and laptop computers, created a more portable and convenient device than a personal new category of “tablet� computers. Just over 14 million computer, with smartphones enjoying stellar growth in iPads were sold in 2011. The launch of the iPad has helped popularity (figure A.9). attract more competitors into the tablet arena, and sales Most mobile internet subscribers in developing coun- of all brands are expected to be close to 300 million by tries are using low-end mobile handsets with minimal 2015. Combined global sales of smartphones and tablet features, which limits their functionality, particularly for computers exceeded those of PCs in 2011 (figure A.8b). the development of advanced information and communi- The outlook for internet connectivity is clearly through a cation technology for development applications. For Key Trends in the Development of the Mobile Sector 123 Figure A.9 Smartphone penetration as a share of Android smartphone to be sold for $150, with the price population, 2011 eventually dropping to under $100. Although those prices will widen the potential target market considerably, such India smartphones will still prove expensive for many Indians, China who “can buy less advanced phones for $40 that have Slovak Rep. Mexico cameras and basic data services� (Sharma 2010). Indonesia Ukraine Turkey Mobile industry Romania Brazil Mobile economy Japan The mobile industry is a significant player in many Thailand national economies. Mobile telecommunication operators Hungary Czech Rep. generated an estimated $848 billion in revenue in 2011 South Africa (figure A.10).9 That is around 1.2 percent of total global Russia annual gross domestic product (GDP) and 56 percent of Malaysia Poland overall telecommunication revenues. The direct economic Belgium impact of the mobile industry varies across regions. While Germany revenue remains at a consistent ratio of around 1 percent France of GDP in most regions, in some developing regions, its Switzerland Canada direct impact is far higher. For instance, in Kenya, financial South Korea transactions via the M-PESA platform are estimated to US equate to up to 20 percent of national GDP (World Bank Portugal Ireland 2010). Greece Mobile communications also has an indirect impact Taiwan, China beyond its direct impact on the economy. The consultancy Austria and accountancy firm Deloitte has developed a framework Netherlands Italy to illustrate the wider impact of the mobile communications UK services sector on the mobile ecosystem (Deloitte 2008). New Zealand Norway Figure A.10 Global telecommunication services Finland market Israel Denmark 1,600 Spain Australia 1,400 Sweden $258 $272 $287 $301 $322 1,200 Billions of US dollars Hong Kong SAR, China Singapore 1,000 0 20 40 60 80 100 800 $728 $758 $798 $848 $896 percent 600 Source: Tomi Ahonen Consulting Analysis, December 2011. http://communi- 400 ties-dominate.blogs.com/brands/2011/12/smartphone-penetration-rates-by- country-we-have-good-data-finally.html. 200 $384 $357 $334 $315 $301 0 2008 2009 2010 2011* 2012** smartphones and tablets to spread more widely and be adopted more rapidly in developing economies, their price Fixed Mobile Data and Internet needs to fall. Google is interested in developing a mass- Source: Adapted from IDATE. market smartphone for emerging nations. It has been *estimate. working with Indian handset manufacturers to develop an **forecast. 124 Information and Communications for Development 2012 This ecosystem includes equipment suppliers, support ser- omy. Based on various economic studies, Deloitte estimates vices, resellers, and retail shops, as well as significant contri- that this multiplier effect ranges from 1.1 to 1.7. butions to government in the form of taxes (figure A.11). The model has been used to calculate the economic Deloitte considers that mobile communications has three impact of mobile communications in a number of coun- indirect economic impacts: tries. One study of six countries in 2007 concluded that the direct economic impact of mobile communications ranged 1. An impact on other industries related to mobile services, from 3.7 to 6.2 percent of national GDP (Deloitte 2008). including network and handset suppliers, airtime The employment impact of mobile communications is resellers, and the like also significant. In addition to the direct employment of 2. An impact on end users from improved productivity, mobile operators, the Deloitte model includes related indus- such as reductions in travel costs, improved job opportu- tries (such as equipment suppliers and airtime resellers), as nities, and greater market efficiency well as spillover employment generated by government taxes and employment created from the consumption expendi- 3. An impact on society related to such benefits as social tures of personnel in mobile-related industries. cohesion, the extension of communications to low- income users, stimulation of local content, and disaster Strategic investors relief assistance The mobile services industry is one of the most globalized In addition, there are multiplier effects throughout the in the world. Practically every developing country has expe- broader economy, as the initial spending related to mobile rienced foreign investment in its mobile cellular market, as communications ripples through other sectors of the econ- have many developed nations. Opening up markets to Figure A.11 Mobile value chain Network Suppliers Other equipment Fixed line of support suppliers of Multiplier suppliers operators (VA) services (VA) capital items (VA) (VA) Airtime sellers and payphone operators (VA) Interconnection Mobile network Government payments operators (VA) tax revenues Handset Fixed line producers operators (VA) and dealers (VA) Payment for mobile services, connections, and handsets Fixed line to mobile calls Payment for handsets End users Source: Deloitte. Note: Value added (VA) is specific to a national economy and does not show international value added. Key Trends in the Development of the Mobile Sector 125 privatization and foreign investment has been a major Many investors are developing a growing geographic factor driving the growth of the mobile industry in emerg- focus and specialization in certain regions. Although only a ing markets. According to the World Bank’s Private Partici- few strategic investors are engaged around the world, most pation in Infrastructure database, between 1990 and 2010, focus on a specific region or geography. South Africa’s MTN, some 329 projects in the mobile telecommunication sector for example, has investments throughout Sub-Saharan in developing regions attracted $441 billion in private Africa and the Middle East. It has grown from operations in sector investment—much of it foreign and most of it from five countries in 2000 and just 2 million subscribers to oper- strategic mobile multinational groups (table A.2). No ations in 21 countries and 142 million subscriptions in 2010. matter the size of a country, its political system, where it is Digicel, which focuses on islands in the Caribbean and located, or its income, private and foreign companies are Pacific, has investments in 32 countries. Some multination- willing to invest in mobile communications. als channel their investments through regional holdings; for The relationship between foreign investors and host example, Vivendi works through Maroc Telecom, France countries has changed considerably in recent years. Telecom through Senegal’s Sonatel, and Vodafone through Publicly held corporations now have to abide by a greater South Africa’s Vodacom. This trend toward regional special- range of regulations and scrutiny relating to management, ization makes investors better informed about their markets accounting, reporting, and governance than in the past. and enhances roaming, potential economies of scale, and Deviating from these rules can have severe repercussions platform-sharing. with investors, governments, and the public. Telenor, the Norwegian strategic investor, was rocked by reports of A Mobile analytical tool poor labor practices in firms that supply its mobile opera- tions in Bangladesh. It immediately implemented reforms This edition of the World Bank Group’s Information and to remedy the situation.10 At the same time, multinationals Communications for Development report features a number are responding to pressing social issues such as the envi- of mobile indicators in both the chapter text and the statis- ronment and poverty by instituting recycling, corporate tical appendix. The wide variety of indicators used can make social responsibility, and similar programs and policies. it difficult to gauge and benchmark country performance. Today, mobile communications markets in many devel- Combining several significant indicators into a smaller oping countries have achieved notable scale. Indeed, some number of composite indicators and tracking changes in developing country subsidiaries now enjoy larger subscriber them over time can provide a useful analytical tool for eval- bases than their foreign investors’ home markets. One is uating the outcomes of different investments and policy Vodafone, where the number of mobile subscriptions in its measures. These composite indicators can also be used to Indian subsidiary is seven times larger than its home market diagnose the strengths and weaknesses of the mobile sector of the United Kingdom. Growth in overseas markets means in a particular country and thereby can serve as a useful tool that investors are responding more to the needs of these for future policy development. The publication of an analyt- overseas markets than previously and leveraging lessons ical tool is consistent with the previous edition of the report, learned abroad to apply throughout their group holdings. which introduced a series of ICT performance measures, Table A.2 Private participation in mobile networks, 1990–2010 Investment commitments in physical assets Region Number of projects (millions of current US$) East Asia and Pacific 45 54,194 Europe and Central Asia 75 87,445 Latin America and the Caribbean 52 153,944 Middle East and North Africa 21 23,538 South Asia 31 69,286 Sub-Saharan Africa 105 52,305 TOTAL 329 440,7132 Sources: World Bank and PPIAF, PPI Project Database. (http://ppi.worldbank.org). 126 Information and Communications for Development 2012 based on country groupings (World Bank 2009). Although networks (universality), the degree to which operators the indicators used in this analytical tool are focused only on provide voice and advanced network services (supply), and the mobile sector, the full range of ICT indicators used in the the ownership and usage of mobile phones (demand). Each performance measures can be found in the World Bank’s composite indicator is constructed from two separate indica- Little Data Book on ICT, the 2012 edition of which is being tors that measure these three components with equal weight published in conjunction with this report. given to each (figure A.12). The three composites could also There have been several methodological approaches and be combined into a single measure if researchers found this compilations of composite mobile indicators. The Interna- useful, but that is not the intention here. The indicators are tional Telecommunication Union (ITU) compiled a one- reproduced in the statistical appendix of this report, provid- time “Mobile/Internet Index� in 2002 (ITU 2002). A ing transparency and allowing users to recreate the analysis.11 framework for a composite mobile indicator with a focus The methodology is similar to that used for the United on the internet has been proposed (Minges 2005). The ITU Nations Development Programme’s Human Development Digital Opportunity Index contained several mobile vari- Index (HDI). Each indicator has an equal weight. Indicators ables and allowed disaggregation into a mobile-only are converted to standardized values based on a logical 100 subcategory (ITU 2006) and was updated in 2007 (ITU and percent “goalpost.� This is a straightforward conversion except UNCTAD 2007). A mobile broadband composite indicator for affordability, which is subtracted from 1 to reflect best has recently been compiled for Latin American nations performance. Although the affordability value may never (A. T. Kearney 2012). None of these composite mobile indi- reach 1 (where mobile service would be free), in 2010 there cators is particularly appropriate for this report because were twenty-six economies where the price of a mobile basket they have either been one-off, are not confined to mobile, was less than 1 percent of per capita income (ITU 2011). or are limited to a particular region. Therefore a specially Table A.3 uses the data for Morocco to provide an exam- constructed mobile analytical tool, based on a series of ple of the construction of the Mobile Analytical Tool. composite indicators and building on the foundation of The analytical tool has been applied to a representative this earlier work, can help to fill the void. range of 100 economies with data availability for the years In the context of the development orientation of the 2005 and 2010 (table A.4 at the end of the appendix). The report, the Mobile Analytical Tool measures, on a country- results provide some interesting insights into the develop- by-country basis, the affordability and coverage of mobile ment of mobile networks over that critical time period. Figure A.12 Mobile analytical tool: indicators and categories 6 indicators 3 categories Percentage of population covered by mobile 1 cellular telephony 1. UNIVERSALITY Mobile cellular tariffs as a percentage of per 2 capita income Mobile cellular subscriptions per 100 people 3 (capped at 100) 2. SUPPLY Ratio of mobile broadband subscriptions to 4 total mobile subscriptions Proportion of households with a mobile 5 phone 3. DEMAND Proportion of individuals that used the 6 internet from a mobile phone Key Trends in the Development of the Mobile Sector 127 Table A.3 Worked example of the mobile analytical tool, Morocco Indicator value Component scores Indicator 2005 2010 2005 2010 Category Percentage of population covered by mobile cellular telephony 98 98 Mobile cellular tariffs as a percentage of per capita income 20.1 14.3 0.88 0.93 Universality Inverted (100-tariff/GNI) 79.9 85.7 Mobile cellular subscriptions per 100 people (capped at 100) 41 100 0.21 0.52 Supply Ratio of mobile broadband subscriptions to total mobile subscriptions 0 4 Proportion of households with a mobile telephone 59 84 0.29 0.44 Demand Proportion of individuals that used the mobile internet 0.04 3.4 Source: Based on Agence Nationale de Réglementation des Télécommunications (ANRT) and Maroc Telecom. Table A.4 Mobile analytical tool components for 100 selected economies, 2005 and 2010 Universality Supply Demand Change Change Change Country 2005 2010 (%) 2005 2010 (%) 2005 2010 (%) Albania 0.86 0.95 10 0.24 0.50 108 0.15 0.49 227 Algeria 0.90 0.96 7 0.21 0.46 119 0.25 0.48 92 Argentina 0.96 0.98 2 0.27 0.52 93 0.35 0.48 37 Armenia 0.95 0.95 0 0.11 0.51 364 0.16 0.49 206 Australia 0.98 0.99 1 0.47 0.70 49 0.44 0.51 16 Austria 0.98 0.99 1 0.55 0.57 4 0.46 0.56 22 Azerbaijan 0.92 0.99 8 0.13 0.42 223 0.26 0.45 73 Bahrain 0.99 0.99 0 0.50 0.51 2 0.50 0.54 8 Bangladesh 0.84 0.97 15 0.03 0.21 600 0.06 0.34 467 Belarus 0.94 0.98 4 0.21 0.51 143 0.15 0.39 160 Belgium 0.99 0.99 0 0.42 0.54 29 0.46 0.49 7 Bolivia 0.73 0.73 0 0.13 0.35 169 0.15 0.40 167 Bosnia and Herzegovina 0.93 0.97 4 0.20 0.43 115 0.27 0.43 59 Brazil 0.90 0.97 8 0.23 0.54 135 0.30 0.43 43 Bulgaria 0.95 0.97 2 0.40 0.52 30 0.36 0.45 25 Cambodia 0.71 0.89 25 0.04 0.34 750 0.11 0.32 191 Cameroon 0.69 0.82 19 0.06 0.20 233 0.14 0.22 57 Canada 0.97 0.99 2 0.26 0.48 85 0.33 0.48 45 Chile 0.97 0.98 1 0.33 0.53 61 0.36 0.48 33 China 0.91 0.98 8 0.15 0.35 133 0.28 0.58 107 Colombia 0.89 0.90 1 0.25 0.50 100 0.28 0.47 68 Costa Rica 0.87 0.87 0 0.13 0.37 185 0.25 0.40 60 Croatia 0.98 0.99 1 0.40 0.52 30 0.40 0.54 35 Czech Republic 0.98 0.99 1 0.50 0.54 8 0.43 0.50 16 Denmark 0.99 0.99 0 0.51 0.73 43 0.50 0.59 18 Ecuador 0.89 0.90 1 0.24 0.52 117 0.19 0.41 116 Egypt, Arab Rep. 0.94 0.98 4 0.09 0.46 411 0.14 0.39 179 Estonia 0.98 0.99 1 0.50 0.59 18 0.42 0.47 12 Finland 0.99 0.99 0 0.51 0.60 18 0.52 0.62 19 France 0.99 0.99 0 0.40 0.64 60 0.38 0.52 37 Georgia 0.93 0.96 3 0.17 0.56 229 0.15 0.43 187 Germany 0.98 0.99 1 0.50 0.59 18 0.39 0.51 31 Ghana 0.61 0.85 39 0.06 0.37 517 0.10 0.37 270 (continued next page) 128 Information and Communications for Development 2012 Table A.4 continued Universality Supply Demand Change Change Change Country 2005 2010 (%) 2005 2010 (%) 2005 2010 (%) Greece 0.99 0.99 0 0.50 0.54 8 0.38 0.47 24 Hong Kong SAR, China 1.00 0.99 –1 0.54 0.72 33 0.46 0.60 30 Hungary 0.98 0.98 0 0.46 0.53 15 0.40 0.48 20 India 0.72 0.86 19 0.03 0.31 933 0.07 0.27 286 Indonesia 0.91 0.96 5 0.10 0.46 360 0.15 0.39 160 Ireland 0.99 0.99 0 0.50 0.65 30 0.45 0.52 16 Israel 0.98 0.99 1 0.51 0.56 10 0.49 0.55 12 Italy 0.99 0.99 0 0.57 0.59 4 0.41 0.55 34 Jamaica 0.96 0.98 2 0.50 0.51 2 0.47 0.50 6 Japan 0.99 0.99 0 0.51 0.94 84 0.72 0.78 8 Jordan 0.95 0.98 3 0.29 0.51 76 0.27 0.55 104 Kazakhstan 0.94 0.97 3 0.16 0.50 213 0.14 0.43 207 Kenya 0.59 0.85 44 0.08 0.36 350 0.11 0.36 227 Korea, Rep. 0.99 0.99 0 0.56 0.96 71 0.58 0.69 19 Kyrgyzstan 0.59 0.90 53 0.05 0.45 800 0.05 0.45 800 Latvia 0.97 0.99 2 0.43 0.65 51 0.42 0.53 26 Lebanon 0.94 0.97 3 0.13 0.37 185 0.25 0.42 68 Lithuania 0.98 0.99 1 0.50 0.58 16 0.37 0.51 38 Macedonia, FYR 0.94 0.96 2 0.31 0.57 84 0.33 0.44 33 Malaysia 0.97 0.99 2 0.38 0.59 55 0.29 0.53 83 Mali 0.19 0.58 205 0.03 0.26 767 0.08 0.11 38 Mauritius 0.99 0.99 0 0.27 0.54 100 0.32 0.51 59 Mexico 0.92 0.95 3 0.22 0.43 95 0.21 0.35 67 Moldova 0.89 0.95 7 0.15 0.47 213 0.16 0.36 125 Morocco 0.88 0.93 6 0.21 0.52 148 0.29 0.44 52 Namibia 0.91 0.96 5 0.10 0.51 410 0.20 0.31 55 Nepal 0.48 0.85 77 0.01 0.16 1,500 0.02 0.30 1,400 Netherlands 0.99 1.00 1 0.50 0.59 18 0.50 0.55 10 New Zealand 0.98 0.98 0 0.46 0.63 37 0.37 0.54 46 Nigeria 0.63 0.79 25 0.07 0.29 314 0.20 0.31 55 Norway 1.00 1.00 0 0.50 0.58 16 0.50 0.56 12 Pakistan 0.71 0.94 32 0.06 0.31 417 0.17 0.25 47 Paraguay 0.84 0.95 13 0.13 0.49 277 0.25 0.44 76 Peru 0.75 0.88 17 0.10 0.49 390 0.11 0.39 255 Philippines 0.89 0.97 9 0.20 0.51 155 0.24 0.43 79 Poland 0.98 0.99 1 0.38 0.66 74 0.33 0.46 39 Portugal 0.99 0.99 0 0.53 0.58 9 0.42 0.47 12 Qatar 0.97 0.99 2 0.45 0.58 29 0.55 0.66 20 Romania 0.96 0.98 2 0.31 0.54 74 0.25 0.41 64 Russian Federation 0.96 0.98 2 0.44 0.52 18 0.16 0.49 206 Rwanda 0.44 0.83 89 0.01 0.19 1,800 0.03 0.20 567 Saudi Arabia 0.95 0.95 0 0.31 0.53 71 0.48 0.53 10 Senegal 0.72 0.85 18 0.07 0.32 357 0.15 0.43 187 Serbia 0.95 0.96 1 0.35 0.54 54 0.36 0.43 19 Singapore 1.00 1.00 0 0.52 0.59 13 0.55 0.61 11 Slovak Republic 0.98 0.98 0 0.42 0.63 50 0.45 0.53 18 Slovenia 0.99 0.99 0 0.45 0.61 36 0.44 0.54 23 South Africa 0.96 0.97 1 0.33 0.53 61 0.31 0.47 52 (continued next page) Key Trends in the Development of the Mobile Sector 129 Table A.4 continued Universality Supply Demand Change Change Change Country 2005 2010 (%) 2005 2010 (%) 2005 2010 (%) Spain 0.99 0.98 –1 0.51 0.59 16 0.42 0.54 29 Sri Lanka 0.87 0.97 11 0.09 0.45 400 0.10 0.32 220 Sweden 0.99 0.99 0 0.52 0.62 19 0.50 0.59 18 Switzerland 0.99 0.99 0 0.48 0.62 29 0.50 0.56 12 Tajikistan 0.20 0.94 370 0.02 0.35 1,650 0.06 0.41 583 Tanzania 0.49 0.77 57 0.05 0.26 420 0.04 0.23 475 Thailand 0.93 0.97 4 0.23 0.51 122 0.36 0.52 44 Turkey 0.97 0.97 0 0.32 0.44 38 0.36 0.49 36 Uganda 0.69 0.85 23 0.03 0.19 533 0.08 0.27 238 Ukraine 0.92 0.98 7 0.32 0.52 63 0.22 0.43 95 United Arab Emirates 0.99 0.99 0 0.50 0.71 42 0.50 0.56 12 United Kingdom 0.99 0.99 0 0.53 0.61 15 0.50 0.57 14 United States 0.99 0.99 0 0.36 0.61 69 0.29 0.56 93 Uruguay 0.95 0.99 4 0.17 0.55 224 0.23 0.37 61 Uzbekistan 0.79 0.95 20 0.01 0.40 3900 0.25 0.44 76 Venezuela, RB 0.90 0.93 3 0.24 0.51 113 0.18 0.26 44 Vietnam 0.89 0.96 8 0.05 0.53 960 0.15 0.29 93 Zambia 0.56 0.78 39 0.04 0.20 400 0.08 0.30 275 Zimbabwe 0.82 0.63 –23 0.03 0.35 1067 0.05 0.27 440 Source: Authors’ analysis. The mean score for all components added together middle-income nations had already achieved near univer- increased by 30 percent between 2005 and 2010, from sality by 2005, and gains since then have been marginal. 0.49 to 0.63, attesting to the rapid growth and improve- Although many developing nations had large increases in ment in mobile networks over that period (figure A.13). universality between 2005 and 2010, many still remain The highest increase was among low-income countries, below the 0.9 threshold. Universal access to mobile where significant gains in coverage were coupled with networks remains constrained in these countries because of falling prices from intensified competition. Regionally, relatively high tariffs, incomplete mobile coverage, or both. the highest growth was in South Asia, followed by Sub- In Mali, for instance, mobile service covers less than half the Saharan Africa. The highest absolute increase was in population, and the price of a monthly basket of mobile Tajikistan, where the score rose by 0.47 points to 0.57. services is one-quarter of per capita income. In Rwanda, Mobile competition intensified in Tajikistan between pricing is a barrier: mobile networks cover more than 90 2005 and 2010, with four GSM (Global System for Mobile percent of the Rwandan population, but a monthly mobile communications) and several CDMA (Code Division basket is 30 percent of per capita income. In India the Multiple Access) operators and a number of panregional bottleneck is coverage: a mobile basket is just 3 percent of mobile groups entering the market, including TeliaSonera per capita income but only three-quarters of the population and Vimpelcom. Investment soared, leading to plummet- is covered. ing prices, an expansion of coverage, and skyrocketing The supply component showed the greatest increase access. Several other Central Asian countries also had between 2005 and 2010, with the mean value nearly among the highest growth in their scores between 2005 doubling from 0.28 to 0.50. In developed countries the and 2010. increase was chiefly attributable to the deployment of Looking at each of the three components individually, mobile broadband networks, whereas gains in developing some 80 countries have achieved a high degree of universal- countries came from the provision of basic voice services. ity (a subindex value of 0.9 or higher). Most developed and Around half of the countries are “stuck� at a supply 130 Information and Communications for Development 2012 Figure A.13 Mobile analytical tool scores, 2005 and 2010, by income and region group 1.0 140 Income group Region Growth, percentage change from 2005 to 2010 0.9 120 Mobile analytical tool score 0.8 0.7 100 0.6 80 0.5 60 0.4 0.3 40 0.2 20 0.1 0.0 0 ld le N gh le w s c sia a sia ca ica ifi ric IA or idd idd Lo fri Hi lA hA ac Af W ED er nA r-m r-m dP tra Am ut M th ra we So pe an en or LD ha dN Up dC Lo ia OR Sa As an an b- W st Su pe st Ea Ea ro Eu le idd M 2005 2010 Growth Source: Author analysis. Note: Scores shown are the mean of the three components. Group averages are the mean of the group. component value of 0.5; there are more SIM cards than Figure A.14 Mobile analytical tool and GNI per people, but the share of mobile broadband is low. capita, 2010 The score achieved on the Mobile Analytical Tool is closely related to gross national income (GNI) per capita 1.0 y = 0.0587Ln(x) + 0.1117 (figure A.14). None of the high-income economies had a 0.9 R2 = 0.7024 KOR JPN score under 0.65, and several upper-middle-income coun- 0.8 tries exceeded that value although with much lower 0.7 incomes. These include the Russian Federation and South KGZ UZB Mobile Index 0.6 MEX Africa along with Argentina, Jamaica, Jordan, Lithuania, TJK VEN 0.5 CRI Macedonia, Malaysia, Mauritius, and Thailand. Japan and NGA the Republic of Korea stand out as outliers—their score is 0.4 ZMB CMR significantly above where it should be considering their 0.3 income. Most countries at very low per capita income aver- 0.2 ages (less than $1,000 a year) fall below the regression line, 0.1 suggesting that a certain level of economic development is necessary for balanced mobile growth. Regional clusters 0.0 $100 $1,000 $10,000 $100,000 are also noticeable: lower-middle-income economies in GNI per capita, US$, 2010 (log scale) Sub-Saharan Africa tend to be performing poorly whereas the opposite is true in Central Asia. A number of Latin Source: Authors’ analysis. Note: Scores shown are the mean of the three components. Each point American upper-middle-income economies are also not represents one economy with outliers highlighted: CMR = Cameroon; CRI doing as well as expected. = Costa Rica; JPN = Japan; KOR = Republic of Korea; KGZ = Kyrgyzstan; MEX = Mexico; NGA = Nigeria; TJK = Tajikistan; UZB = Uzbekistan; VEN = Venezuela, RB; ZMB = Zambia. Key Trends in the Development of the Mobile Sector 131 Figure A.15 Mobile analytical tool: China and Sri Lanka compared a. Supply and demand b. Overall values for China and Sri Lanka 0.9 Coverage y = 0.8294x + 0.0683 1.0 0.8 R2 = 0.8185 0.8 0.7 0.6 Mobile Afford- Supply component 0.6 Internet % 0.4 ability 0.2 0.5 Sri Lanka 0 0.4 China 0.3 Household % SIM per 0.2 100 0.1 0.0 Broadband % 0.0 0.2 0.4 0.6 0.8 1.0 Demand component China Sri Lanka Source: Authors’ analysis. As might be expected, there is a close relationship In contrast, Sri Lanka scores higher on the supply compo- between the supply and demand categories (figure A.15a). nent (0.45) than on the demand one (0.32). On the supply Outliers illustrate mismatches between supply and demand. side, there is a high degree of competition in the Sri Lankan For example in China the demand component (0.58) is mobile market with SIM card penetration at 85 per 100 higher than the supply component (0.35), suggesting further people. Further, Sri Lanka was the first South Asian nation to room for growth (figure A.15b). Over 90 percent of Chinese launch mobile broadband networks. On the demand side, households have a mobile phone, the second-highest level however, the penetration of mobile phones in Sri Lankan among the developing countries used in the Mobile Analyt- homes is only 60 percent and just 5 of every 100 people use ical Tool (Jordan has the highest home mobile penetration a mobile phone to access the internet (see figure A.15b). The among this group). China also has a relatively high level of mismatch suggests that efforts here need to be devoted to internet access through mobile phones. According to a boosting demand. recent 21-country survey, some 37 percent of Chinese Figure A.16 illustrates the relationship between the mobile phone owners use their handset to access the inter- three composite indicators and underlying indicators of net, a higher ratio than in France, Germany, or Spain.12 On the Mobile Analytical Tool. The values for high-income the supply side, China’s SIM card penetration is only 64 per economies are contrasted with the world and low- and 100 people, relatively low because there are few incentives for middle-income averages. As noted, high degrees of univer- multiple SIM card ownership thanks to inexpensive cross sality have been achieved with high affordability and network pricing. China is relatively new to mobile broad- second-generation (2G) coverage. There have also been band with networks having launched only in 2009. Subscrip- large gains in supply of 2G networks and household tions to high-speed mobile networks have grown rapidly, demand between 2005 and 2010. However, levels of mobile and by the end of 2010 China had the third-largest number broadband networks and internet usage are low, and these of mobile broadband users in the world (after Japan and the will be the growth areas in the future. Care is needed to United States). Nevertheless, mobile broadband still ensure that an advanced mobile digital divide does not accounted for only 5 percent of total mobile subscriptions, develop as a result of restricted mobile broadband coverage with the result that most Chinese mobile internet users were (such as poor coverage in rural areas) and limited mobile accessing the web over narrowband mobile connections. broadband affordability. 132 Information and Communications for Development 2012 Figure A.16 Mobile analytical tool components summarized 1.00 0.64 0.72 0.75 0.63 Global 0.58 0.49 values 0.50 0.40 0.25 0 2005 2010 0.99 0.99 0.95 0.92 1.00 0.88 0.83 0.75 0.62 0.55 0.47 0.50 0.44 0.46 0.45 0.40 0.50 0.28 0.29 0.25 0.18 0.20 0 2005 2010 2005 2010 2005 2010 Universality Supply Demand 98 99 94 99 99 95 93 99 100 88 91 91 88 83 93 88 83 84 82 81 74 75 55 56 50 40 35 25 25 17 12 7 3 10 5 4 1 0 5 1 0 2005 2010 2005 2010 2005 2010 2005 2010 2005 2010 2005 2010 Coverage Affordability Subscriptions Broadband Households Internet High income World Low & middle income Source: Authors’ analysis. Note: The scores shown at the top are based on the mean of the three components of the Mobile Analytical Tool. The Mobile Analytical Tool provides different insights mobile network development compared with using single into the availability and demand for mobile communica- indicators to measure performance. tions. It overcomes the limitations of using a single indi- cator to gauge mobile performance. For example, the Notes number of mobile subscriptions is often used as a comparator of development, but it can be misleading 1. “The importance of availability of information communica- because of underlying variations in multiple SIM card tion technology (ICT) devices is increasing significantly in contemporary society. These devices provide a set of services ownership, which in turn reflects interoperator pricing that are changing the structure and pattern of major social strategies. As the case of China and Sri Lanka illustrated, and economic phenomena. The housing census provides an Sri Lanka has a higher SIM card penetration but much outstanding opportunity to assess the availability of these lower rates of actual mobile ownership and internet devices to the household� (United Nations 2008, 215). browsing from cell phones. The Mobile Analytical Tool 2. A major factor has been the development of low-cost models: “... provides a holistic and integrated perspective of country the spread of mobile phones in developing countries has been Key Trends in the Development of the Mobile Sector 133 accompanied by the rise of homegrown mobile operators in ITU (International Telecommunication Union). 2002. “Hong China, India, Africa and the Middle East that rival or exceed the Kong (China) and Denmark Top ITU Mobile/Internet Index.� industry’s Western incumbents in size. These operators have Press release (September 17). http://www.itu.int/newsroom developed new business models and industry structures that /press_releases/2002/20.html. enable them to make a profit serving low-spending customers ———. 2006. “Digital Opportunity Index (DOI).� http://www.itu that Western firms would not bother with� (Standage 2009). .int/ITU-D/ict/doi/index.html. 3. This is derived from the 22 percent of the population in ———. 2011. “Measuring the Information Society.� http://www low- and middle-income economies who lived on less than .itu.int/ITU-D/ict/publications/idi/index.html. $1.25 a day in 2008 (at 2005 international prices); see ITU and UNCTAD (United Nations Conference for Trade and http://data.worldbank.org/indicator/SI.POV.DDAY. Development). 2007. “World Information Society Report: 4. http://lirneasia.net/2011/06/nokia-annual-tco-total-cost-of- Beyond WSIS.� http://www.itu.int/osg/spu/publications ownership-results-show-bangladesh-and-sri-lanka-as- /worldinformationsociety/2007/. cheapest/. Minges, M. 2005. “Is the Internet Mobile? Measurements from the 5. “Movirtu Rolls Out a Cloud Phone Aimed at Low-Income Asia-Pacific Region.� Telecommunications Policy 29 (2–3): Users: First Market Is Madagascar, Others Will Follow.� 113–125. doi:10.1016/j.telpol.2004.11.002. Balancing Act, June 24, 2011. http://www.balancingact-africa .com/news/en/issue-no-560/top-story/movirtu-rolls-out- Nokia. 2009. “Tailoring Mobile Costs to the Pockets of a Billion a/en. New Customers.� Expanding Horizons. Q2 2009 edition. http:// www.nokiasiemensnetwor ks.com/sites/default/files 6. http://www.gartner.com/it/page.jsp?id=1893523. /document/Expanding_Horizons_2_2009_0.pdf. 7. http://www.c-i-a.com/methodology.htm#computeruse. OECD (Organisation for Economic Co-operation and Develop- 8. http://www.gartner.com/it/page.jsp?id=1924314. ment). 2010. Wireless Broadband Indicator Methodology. Paris 9. http://blog.idate.fr/?p=133. (March 18). http://www.oecd.org/LongAbstract/0,3425, 10. “Improving HSSE Standards: The Case of Bangladesh.� http:// en_2649_34225_44930927_119666_1_1_1,00.html. www.telenor.com/en/corporate-responsibility/initiatives- Sharma, Amol. 2010. “Google Bets on Cheap Smartphones for worldwide/improving-hsse-standards-bangladesh. India.� WSJ.com , October 12. http://online.wsj.com 11. Note that the Mobile Analytical Tool was calculated prior to /article/SB100014240527487037941045755459631086151 final data updates and the results for some countries would 20.html. differ if there were later data revisions. Standage, T. 2009. “Mobile Marvels.� The Economist, September 26. 12. http://www.pewglobal.org/2011/12/20/global-digital-communi UAE Telecommunications Regulatory Authority. 2011. ICT in the cation-texting-social-networking-popular-worldwide/. UAE: Household Survey, 2010. United Nations. 2008. “Principles and Recommendations for Population and Housing Censuses, Revision 2.� http:// References unstats.un.org/unsd/demographic/sources/census/census3 Akamai. 2012. “The State of the Internet: 3rd Quarter, 2011 .htm. Report.� http://www.akamai.com/html/about/press/releases/ Vodacom. 2011. “Integrated Report for the Year Ended 31 March 2012/press_013112.html. 2011.� A. T. Kearney. 2012. “Latin American Mobile Observatory 2011.� World Bank. 2009. “ICT Performance Measures: Methodology and GSMA. http://www.gsma.com/documents/download-full-report- Findings.� In Information and Communication for Development english-pdf-5-3-mb/21905. 2009. Extending Reach and Increasing Impact. Washington, DC. Deloitte. 2008. “Economic Impact of Mobile Communications in www.worldbank.org/ic4d. Serbia, Ukraine, Malaysia, Thailand, Bangladesh and Pakistan.� ———. 2010. “Kenya Economic Update: Kenya at the Tipping http://www.telenor.rs/media/TelenorSrbija/fondacija/economic Point.� No. 3, Washington (December). http://siteresources _impact_of_mobile_communications.pdf. .worldbank.org/KENYAEXTN/Resources/KEU-Dec_ Grameenphone. 2011. Annual Report 2010. http://investor- 2010_with_cover_e-version.pdf. relations.grameenphone.com/Annual-Reports.html. ———. 2011. “Little Data Book on Information and Communi- GSMA. 2009. “GSMA Urges Bangladesh Government to Eliminate cation Technology.� http://siteresources.worldbank.org/ SIM Card Tax ~ GSM World.� Press release (July 22). http://www INFORMATIONANDCOMMUNICATIONANDTECH .gsmworld.com/newsroom/press-releases/2009/3493.htm. NOLOGIES/Resources/ICT_Little_Data2011.pdf. 134 Information and Communications for Development 2012 Data Notes Kaoru Kimura and Michael Minges The World Bank’s Mobile At-a-Glance Country Tables present Aggregate measures for income groups in one place the most recent country-specific mobile cellular and regions data from many sources. The data offer a snapshot of the The aggregate measures for income groups include 216 economic and social context and the structure and perform- economies (those economies listed in the At-a-Glance ance of the mobile cellular sector in some 152 economies. Country Tables plus those in the Other Economies table) wherever data are available. The aggregate measures for regions include only low- and Tables middle-income economies (note that these measures Economies are presented alphabetically. Data are shown include developing economies with populations of less than for 152 economies with populations of more than 1 million 1 million, including those listed in the Other Economies for which timely and reliable information exists. The table). The country composition of regions is based on the table Key Mobile Indicators for Other Economies presents World Bank’s analytical regions and may differ from data for 64 additional economies—those with sparse data, common geographic usage. smaller economies with populations of between 30,000 and 1 million, and others that are not members of the World Bank Group. Charts The data in the tables are categorized into three The Mobile Cellular Subscriptions chart shows the sections: number of mobile subscribers (per 100 people) from 2005 to 2011. Country and region information is presented • Economic and social context provides a snapshot of the when available. economy’s macroeconomic and social environment. The mobile basket chart shows the mobile prepaid tariff Several indicators have been included that relate to the basket (% of GNI per capita) in the country from 2005 to different sectors discussed in the report. 2010. Country and region information is presented when • Sector structure provides an overview of the competitive available. market status in the mobile cellular sector. • Sector performance provides statistical data on the mobile Data consistency and reliability cellular sector with indicators for access, usage, and Considerable effort has been made to standardize the data affordability. collected. Full comparability of data among countries 135 cannot be ensured, however, and care must be taken in inter- Classification of economies preting the indicators. For operational and analytical purposes, the World Bank’s Many factors affect availability, comparability, and relia- main criterion for classifying economies is GNI (gross bility: statistical systems in some developing countries are national income) per capita. Every economy is classified as weak; statistical methods, coverage, practices, and defini- low income, middle income (these are subdivided into lower tions differ widely among countries; and cross-country and middle and upper middle), or high income. Note that classi- intertemporal comparisons involve complex technical and fication by incomes does not necessarily reflect development conceptual problems that cannot be unequivocally resolved. status. Because GNI per capita changes over time, the coun- Data coverage may not be complete because of special try composition of income groups may change, but one circumstances or because economies are experiencing prob- consistent classification, based on GNI per capita in 2010, is lems (such as those stemming from conflicts) that affect the used throughout this publication. collection and reporting of data. For these reasons, although Low-income economies are those with a GNI per capita data are drawn from the sources thought to be most author- of $1,005 or less in 2010. Middle-income economies are itative, they should be construed only as indicating trends those with a GNI per capita of more than $1,005 but less and characterizing major differences among economies than $12,276. Lower-middle-income and upper-middle- rather than offering precise quantitative measures of those income economies are separated at a GNI per capita of differences. $3,975. High-income economies are those with a GNI per Administrative subscription-based data generally refer to capita of $12,276 or more. the end of the calendar year. If end-of-year data are not For more information on these classifications, see the available, the most recent data for that year are used. Survey- Classification of Economies by Income and Region table based data refer to the year the survey was carried out. In below and the World Bank’s country classification website: some cases estimates have been made when there is suffi- http://data.worldbank.org/about/country-classifications. cient historical data. The cut-off date for data inclusion was March 31, 2012. Symbols The following symbols are used throughout the At-a-Glance Data sources tables: Data are drawn from ictDATA.org, International Monetary — This symbol means that data are not available or that Fund (IMF), International Telecommunication Union aggregates cannot be calculated because of missing data in (ITU), United Nations; United Nations Educational, Scien- the year shown. tific and Cultural Organization (UNESCO), Institute for 0 or 0.0 means zero or less than half the unit shown. Statistics (UIS), Wireless Intelligence, World Health Organi- $ refers to U.S. dollars, unless otherwise stated. zation (WHO), and the World Bank. 136 Information and Communications for Development 2012 Classification of Economies by Region and Income, FY 2012 East Asia and the Pacific Costa Rica (UMC) Comoros (LIC) American Samoa (UMC) Cuba (UMC) Congo, Dem. Rep. (LIC) Cambodia (LIC) Dominica (UMC) Congo, Rep. (LMC) China (UMC) Dominican Republic (UMC) Côte d’Ivoire (LMC) Fiji (LMC) Ecuador (UMC) Eritrea (LIC) Indonesia (LMC) El Salvador (LMC) Ethiopia (LIC) Kiribati (LMC) Grenada (UMC) Gabon (UMC) Korea, Dem. Rep. (LIC) Guatemala (LMC) Gambia, The (LIC) Lao PDR (LMC) Guyana (LMC) Ghana (LMC) Malaysia (UMC) Haiti (LIC) Guinea (LIC) Marshall Islands (LMC) Honduras (LMC) Guinea-Bissau (LIC) Micronesia, Fed. Sts. (LMC) Jamaica (UMC) Kenya (LIC) Mongolia (LMC) Mexico (UMC) Lesotho (LMC) Myanmar (LIC) Nicaragua (LMC) Liberia (LIC) Palau (UMC) Panama (UMC) Madagascar (LIC) Papua New Guinea (LMC) Paraguay (LMC) Malawi (LIC) Philippines (LMC) Peru (UMC) Mali (LIC) Samoa (LMC) St. Kitts and Nevis (UMC) Mauritania (LMC) Solomon Islands (LMC) St. Lucia (UMC) Mauritius (UMC) Thailand (UMC) St. Vincent and the Grenadines (UMC) Mayotte (UMC) Timor-Leste (LMC) Suriname (UMC) Mozambique (LIC) Tonga (LMC) Uruguay (UMC) Namibia (UMC) Tuvalu (LMC) Venezuela, RB (UMC) Niger (LIC) Vanuatu (LMC) Nigeria (LMC) Middle East and North Africa Vietnam (LMC) Rwanda (LIC) Algeria (UMC) São Tomé and Principe (LMC) Europe and Central Asia Djibouti (LMC) Senegal (LMC) Albania (UMC) Egypt, Arab Rep. (LMC) Seychelles (UMC) Armenia (LMC) Iran, Islamic Rep. (UMC) Sierra Leone (LIC) Azerbaijan (UMC) Iraq (LMC) Somalia (LIC) Belarus (UMC) Jordan (UMC) South Africa (UMC) Bosnia and Herzegovina (UMC) Lebanon (UMC) South Sudan (LMC) Bulgaria (UMC) Libya (UMC) Sudan (LMC) Georgia (LMC) Morocco (LMC) Swaziland (LMC) Kazakhstan (UMC) Syrian Arab Republic (LMC) Tanzania (LIC) Kosovo (LMC) Tunisia (UMC) Togo (LIC) Kyrgyz Republic (LIC) West Bank and Gaza (LMC) Uganda (LIC) Latvia (UMC) Yemen, Rep. (LMC) Zambia (LMC) Lithuania (UMC) South Asia Zimbabwe (LIC) Macedonia, FYR (UMC) Moldova (LMC) Afghanistan (LIC) High income OECD Montenegro (UMC) Bangladesh (LIC) Australia Romania (UMC) Bhutan (LMC) Austria Russian Federation (UMC) India (LMC) Belgium Serbia (UMC) Maldives (UMC) Canada Tajikistan (LIC) Nepal (LIC) Czech Republic Turkey (UMC) Pakistan (LMC) Denmark Turkmenistan (LMC) Sri Lanka (LMC) Estonia Ukraine (LMC) Finland Sub-Saharan Africa Uzbekistan (LMC) France Angola (LMC) Latin America and the Caribbean Benin (LIC) Germany Antigua and Barbuda (UMC) Botswana (UMC) Greece Argentina (UMC) Burkina Faso (LIC) Hungary Belize (LMC) Burundi (LIC) Iceland Bolivia (LMC) Cameroon (LMC) Ireland Brazil (UMC) Cape Verde (LMC) Israel Chile (UMC) Central African Republic (LIC) Italy Colombia (UMC) Chad (LIC) Japan (continued next page) Data Notes 137 Classification of Economies by Region and Income, FY 2012 continued Korea, Rep. Bahrain Macao SAR, China Luxembourg Barbados Malta Netherlands Bermuda Monaco New Zealand Brunei Darussalam New Caledonia Norway Cayman Islands Northern Mariana Islands Poland Channel Islands Oman Portugal Croatia Puerto Rico Slovak Republic Curaçao Qatar Slovenia Cyprus San Marino Spain Equatorial Guinea Saudi Arabia Sweden Faeroe Islands Singapore Switzerland French Polynesia Sint Maarten (Dutch part) United Kingdom Gibraltar St. Martin (French part) United States Greenland Taiwan, China Guam Trinidad and Tobago Other high income Hong Kong SAR, China Turks and Caicos Islands Andorra Isle of Man United Arab Emirates Aruba Kuwait Virgin Islands (U.S.) Bahamas, The Liechtenstein Source: World Bank. Note: This table classifies all World Bank member economies and all other economies with populations of more than 30,000. Economies are divided among income groups according to 2010 GNI per capita, calculated using the World Bank Atlas method. The groups are: low-income countries (LIC), $1,005 or less; lower-middle-income countries (LMC), $1,006–$3,975; upper-middle-income countries (UMC), $3,976–$12,275; and high-income countries, $12,276 or more. Definitions and data sources Expected years of schooling (years) are the number of years a child of school entrance age is expected to spend at This section provides definitions and sources of the indicators school, or university, including years spent on repetition. It used in the World Bank’s Mobile At-a-Glance Country Tables. is the sum of the age-specific enrollment ratios for primary, secondary, postsecondary nontertiary, and tertiary educa- Economic and social context tion. (UNESCO Institute for Statistics) Population (total, million) is based on the de facto defi- Physicians density (per 1,000 people) refers to the nition of population, which counts all residents regardless number of physicians (including generalists and specialist of legal status or citizenship—except for refugees not medical practitioners) (WHO). permanently settled in the country of asylum, who are Depositors with commercial banks (per 1,000 adults) generally considered part of the population of their coun- are the reported number of deposit account holders at try of origin. The values shown are mid-year estimates. commercial banks and other resident banks functioning as (World Bank) commercial banks that are resident nonfinancial corpora- GNI per capita, World Bank Atlas method (current tions (public and private). For many countries data cover US$) is gross national income converted to U.S. dollars using the total number of deposit accounts because information the World Bank Atlas method, divided by the mid-year on account holders is lacking. The major types of deposits population. GNI is the sum of value added by all resident are checking accounts, savings accounts, and time producers plus any product taxes (less subsidies) not deposits. (IMF) included in the valuation of output plus net receipts of primary income (compensation of employees and property Sector structure income) from abroad. (World Bank) Number of mobile operators refers to licensed mobile cellular Rural population (% of total) refers to people living in service providers that have their own network infrastructure as rural areas as defined by national statistical offices. It is opposed to other mobile service providers who lease it (for calculated as the difference between total population and example, Mobile Virtual Network Operators). The data refer to urban population. (United Nations) nationwide operators. (ictDATA.org) 138 Information and Communications for Development 2012 Herfindahl–Hirschman Index (HHI) (scale = 0–10,000) technologies: CDMA2000 1xEV-DO, W-CDMA, TD-SCDMA, refers to the level of market concentration. It is calculated on LTE, and mobile WiMAX. (Wireless Intelligence) the basis of the market shares of each company operating in Mobile broadband (% of total mobile subscriptions) is the industry. The market share for each company is squared; the number of mobile broadband subscribers (defined these are then added up to get the HHI. A monopoly market above) divided by the total mobile cellular subscriptions in a would have an HHI of 10,000; a duopoly with each operator country. (Wireless Intelligence) having half the market would have an HHI of 5,000; and a market with four operators each having the same market Usage share would have an HHI of 2,500. The HHI is computed for Households with a mobile telephone (%) refers to the the mobile market based on the number of subscribers. percentage of households reporting ownership of a mobile (ictDATA.org) cellular telephone. (ictDATA.org) Mobile voice usage (minutes per user per month) mea- Sector performance sures the minutes of use per mobile user per month. Access (Wireless Intelligence) Mobile cellular subscriptions (per 100 people) are Population using mobile internet (%) refers to the share subscriptions to a public mobile telephone service using of people using a mobile phone to access the internet cellular technology, which provide access to the public (regardless of speed or technology). The data are derived switched telephone network. Postpaid and prepaid subscrip- from both mobile and internet user surveys and therefore tions are included. Note that data is not strictly comparable the figure is shown as a percentage of the total population. because of differences in the period in which a subscriber is In cases where survey data are not available, subscription considered active and whether nonhuman subscriptions data (that is, mobile internet subscribers) have been used. (such as data cards for laptop access or automatic teller (ictDATA.org) machines) are included. For these reasons and others, Short message service (SMS) users (% of mobile users) mobile subscriptions do not reflect actual mobile phone refers to the percentage of mobile users who send SMS text ownership since there can be multiple subscriptions. (ITU, messages. (ictDATA.org) ictDATA.org) Mobile cellular subscriptions (% prepaid) refer to the Affordability total number of mobile cellular telephone subscriptions Mobile basket (US$ a month) is based on the Organisation that use prepaid refills. These are subscriptions where, for Economic Co-operation and Development’s updated instead of paying an ongoing monthly fee, users purchase basket for low users (retrofitted also for 2005), which blocks of usage time. Only active subscriptions should be includes the cost of monthly mobile use for 30 outgoing included (those used at least once in the last three months calls a month spread over the same mobile network, other for making or receiving a call or carrying out a nonvoice mobile networks, and mobile-to-fixed-line calls and during activity such as sending or reading an SMS or accessing the peak, off-peak, and weekend times as well as 100 text internet). The number of prepaid subscriptions is divided messages a month. (ictDATA.org for 2005 data, ITU for by total mobile cellular telephone subscriptions. (Wireless 2010 data). For more information on the definition, see Intelligence) ITU, 2011, Measuring the Information Society. Annex Table Population covered by a mobile-cellular network (%) is 2.1, p 144–45, http://www .itu.int/net/pressoffice/back- the percentage of people within range of a mobile cellular grounders/general/pdf/5.pdf. signal regardless of whether they are subscribers. (ITU) Mobile tariff basket (% of GNI per capita) refers to the Mobile broadband subscriptions (per 100 people) are the mobile cellular prepaid monthly tariff basket divided by sum of the number of subscriptions using the following GNI per capita. (ictDATA.org, ITU, and World Bank) Data Notes 139 World Bank • Mobile at a Glance Albania Europe & Upper-middle- Central Asia Albania income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 3 3 2,452 405 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,580 3,960 5,886 7,272 150 Rural population (% of total) 55 52 43 36 Expected years of schooling (years) 11 — 13 13 120 Physicians density (per 1,000 people) 1.2 1.2 1.7 3.2 90 Depositors with commercial banks (per 1,000 adults) — — — 894 60 Sector structure 30 Number of mobile operators — 4 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,661 0 2005 2007 2009 2011 Albania Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 49 138 92a 125a Mobile cellular subscriptions (% prepaid) 97 91a 81a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 91 98 99 96 25 Mobile broadband subscriptions (per 100 people) — 5.6a 14.3a 22.6a 20 Mobile broadband (% of total mobile subscriptions) — 3.5a 15.4a 18.0a Usage 15 Households with a mobile telephone (%) 31 94 84 82 10 Mobile voice usage (minutes per user per month) 64 103 325a 288a Population using mobile Internet (%) — 3.4 22.9a 8.5 5 Short Message Service (SMS) users (% of mobile users) — 66.0 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Albania Mobile basket (% of GNI per capita) 22.6 7.8 2.9 3.1 Europe & Central Asia Region Algeria Middle East & Upper-middle- North Africa Algeria income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 33 35 2,452 331 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,720 4,390 5,886 3,874 150 Rural population (% of total) 37 34 43 42 Expected years of schooling (years) 13 14 13 12 120 Physicians density (per 1,000 people) 1.2 — 1.7 1.4 90 Depositors with commercial banks (per 1,000 adults) 315 346 — 443 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,409 2005 2007 2009 2011 Algeria Sector performance Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 42 78a 92a 89a Mobile cellular subscriptions (% prepaid) 98 96a 81a 87a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 42 — 99 — 10 Mobile broadband subscriptions (per 100 people) — — 14.3a — Mobile broadband (% of total mobile subscriptions) — — 15.4a — 8 Usage 6 Households with a mobile telephone (%) 47 94 84 — 4 Mobile voice usage (minutes per user per month) 139 182 325a — 2 Population using mobile Internet (%) — 2.7 22.9a 4.5 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Algeria Mobile basket (% of GNI per capita) 7.7 3.4 2.9 3.6 Middle East & North Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 141 World Bank • Mobile at a Glance Angola Lower-middle- Sub-Saharan Angola income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 16 19 2,519 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,330 3,960 1,623 1,188 150 Rural population (% of total) 46 42 61 63 120 Expected years of schooling (years) 9 — 10 9 Physicians density (per 1,000 people) 0.1 — 0.8 0.2 90 Depositors with commercial banks (per 1,000 adults) 35 97 — 167 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,638 2005 2007 2009 2011 Angola Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 10 58a 78a 57a Mobile cellular subscriptions (% prepaid) 99 99a 96a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 40 — 86 72 60 Mobile broadband subscriptions (per 100 people) 0.1 10.1a 7.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) 0.3 16.5a 9.0a 10.1a 40 Usage 30 Households with a mobile telephone (%) 26 52 77 52 20 Mobile voice usage (minutes per user per month) 141 108 276a — 10 Population using mobile Internet (%) — — 2.9 — Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Angola Mobile basket (% of GNI per capita) 10.0 5.8 7.2 19.5 Sub-Saharan Africa Region Argentina Latin America & Upper-middle- the Caribbean Argentina income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 39 40 2,452 583 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 4,460 8,620 5,886 7,741 150 Rural population (% of total) 9 8 43 21 120 Expected years of schooling (years) 15 16 13 14 Physicians density (per 1,000 people) 3.2 — 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) 524 702 — — 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,351 0 2005 2007 2009 2011 Sector performance Argentina Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 57 141a 92a 109a Mobile cellular subscriptions (% prepaid) 70 71a 81a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 94 — 99 98 7 Mobile broadband subscriptions (per 100 people) — 18.8a 14.3a 16.1a 6 Mobile broadband (% of total mobile subscriptions) — 13.7a 15.4a 15.2a 5 Usage 4 Households with a mobile telephone (%) 67 86 84 84 3 Mobile voice usage (minutes per user per month) 139 100a 325a 141a 2 Population using mobile Internet (%) — 10.6 22.9a 4.4 1 Short Message Service (SMS) users (% of mobile users) — 97.0a 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Argentina Mobile basket (% of GNI per capita) 3.6 4.3 2.9 3.7 Latin America & the Caribbean Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 142 Information and Communications for Development 2012 World Bank • Mobile at a Glance Armenia Europe & Lower-middle- Central Asia Armenia income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 3 3 2,519 405 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,470 3,200 1,623 7,272 150 Rural population (% of total) 36 36 61 36 120 Expected years of schooling (years) 11 12 10 13 Physicians density (per 1,000 people) 3.7 3.8 0.8 3.2 90 Depositors with commercial banks (per 1,000 adults) 357 589 — 894 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,993 0 2005 2007 2009 2011 Armenia Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 10 122a 78a 125a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 87 86a 96a 82a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 85 99 86 96 20 Mobile broadband subscriptions (per 100 people) — 9.8a 7.3a 22.6a Mobile broadband (% of total mobile subscriptions) — 9.3a 9.0a 18.0a 15 Usage 10 Households with a mobile telephone (%) 33 91 77 82 Mobile voice usage (minutes per user per month) 121 344a 276a 288a 5 Population using mobile Internet (%) — 7.4 2.9 8.5 Short Message Service (SMS) users (% of mobile users) — 31.0 61.9a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Armenia Mobile basket (% of GNI per capita) 17.8 3.3 7.2 3.1 Europe & Central Asia Region Australia High-income Australia group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 20 22 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 30,440 46,200 38,746 150 Rural population (% of total) 12 11 22 120 Expected years of schooling (years) 20 20 16 Physicians density (per 1,000 people) 1.0 3.0 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,433 0 2005 2007 2009 2011 Australia Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 90 130a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 49 47a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 98 99 100 2.0 Mobile broadband subscriptions (per 100 people) 4.2 97.7a 69.6a Mobile broadband (% of total mobile subscriptions) 4.5 74.4a 57.6a 1.5 Usage 1.0 Households with a mobile telephone (%) 83 88 93 Mobile voice usage (minutes per user per month) 109 131a 339 0.5 Population using mobile Internet (%) 4.9 13.9 24.3 Short Message Service (SMS) users (% of mobile users) — 86.0a 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Australia Mobile basket (% of GNI per capita) 1.3 0.7 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 143 World Bank • Mobile at a Glance Austria High-income Austria group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 8 8 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 37,210 47,030 38,746 180 Rural population (% of total) 34 32 22 150 Expected years of schooling (years) 15 15 16 120 Physicians density (per 1,000 people) 3.7 4.9 2.8 Depositors with commercial banks (per 1,000 adults) 1,420 1,376 — 90 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,339 2005 2007 2009 2011 Austria Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 105 157a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 36 26a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 99 100 1.8 Mobile broadband subscriptions (per 100 people) 10.7 83.3a 69.6a 1.5 Mobile broadband (% of total mobile subscriptions) 10.4 54.9a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 88 91 93 0.6 Mobile voice usage (minutes per user per month) — 181a 339 Population using mobile Internet (%) 3.6 20.3 24.3 0.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability Austria Mobile basket (% of GNI per capita) 1.7 0.4 1.0 High-income group Azerbaijan Europe & Upper-middle- Central Asia Azerbaijan income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 8 9 2,452 405 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,270 5,330 5,886 7,272 150 Rural population (% of total) 49 48 43 36 Expected years of schooling (years) 12 12 13 13 120 Physicians density (per 1,000 people) 3.6 3.8 1.7 3.2 90 Depositors with commercial banks (per 1,000 adults) 18 41 — 894 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,780 0 2005 2007 2009 2011 Azerbaijan Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 27 84a 92a 125a Mobile cellular subscriptions (% prepaid) 96 94a 81a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 99 96 20 Mobile broadband subscriptions (per 100 people) — 4.5a 14.3a 22.6a Mobile broadband (% of total mobile subscriptions) — 4.6a 15.4a 18.0a 15 Usage 10 Households with a mobile telephone (%) 50 80 84 82 Mobile voice usage (minutes per user per month) 66 114 325a 288a 5 Population using mobile Internet (%) — 1.3 22.9a 8.5 Short Message Service (SMS) users (% of mobile users) — 26.0 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Azerbaijan Mobile basket (% of GNI per capita) 18.5 1.6 2.9 3.1 Europe & Central Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 144 Information and Communications for Development 2012 World Bank • Mobile at a Glance Bahrain High-income Bahrain group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 0.72 1 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 17,400 18,730 38,746 150 Rural population (% of total) 12 11 22 120 Expected years of schooling (years) — — 16 Physicians density (per 1,000 people) 2.7 1.4 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,354 2005 2007 2009 2011 Bahrain Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 106 128a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 83 79a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 1.5 Mobile broadband subscriptions (per 100 people) 0.6 41.8a 69.6a 1.2 Mobile broadband (% of total mobile subscriptions) 0.6 29.8a 57.6a 0.9 Usage Households with a mobile telephone (%) 95 99 93 0.6 Mobile voice usage (minutes per user per month) — — 339 0.3 Population using mobile Internet (%) 5.5 8.7 24.3 Short Message Service (SMS) users (% of mobile users) — 80.0a 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Bahrain Mobile basket (% of GNI per capita) 1.0 0.9 1.0 High-income group Bangladesh Low-income South Asia Bangladesh group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 141 149 796 1,633 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 480 700 530 1,176 150 Rural population (% of total) 74 72 72 70 120 Expected years of schooling (years) 8 — 9 10 Physicians density (per 1,000 people) 0.3 — 0.2 0.6 90 Depositors with commercial banks (per 1,000 adults) 321 418 — 249 60 Sector structure 30 Number of mobile operators — 6 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,067 2005 2007 2009 2011 Bangladesh Sector performance South Asia Region Access Mobile cellular subscriptions (per 100 people) 6 57a 43a 67a Mobile cellular subscriptions (% prepaid) 95 98a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 80 — — 84 18 Mobile broadband subscriptions (per 100 people) — — — 3.3a 15 Mobile broadband (% of total mobile subscriptions) — — — 4.6a 12 Usage 9 Households with a mobile telephone (%) 11 64 43 54 6 Mobile voice usage (minutes per user per month) 235 210a — 305a Population using mobile Internet (%) — — — 3.3a 3 Short Message Service (SMS) users (% of mobile users) — 30.0 — 47.0a 0 2005 2006 2007 2008 2009 2010 Affordability Bangladesh Mobile basket (% of GNI per capita) 16.3 3.4 28.8 3.2 South Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 145 World Bank • Mobile at a Glance Belarus Europe & Upper-middle- Central Asia Belarus income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 10 9 2,452 405 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,780 5,950 5,886 7,272 150 Rural population (% of total) 28 26 43 36 Expected years of schooling (years) 14 — 13 13 120 Physicians density (per 1,000 people) 4.7 5.2 1.7 3.2 90 Depositors with commercial banks (per 1,000 adults) — — — 894 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,889 0 2005 2007 2009 2011 Belarus Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 42 119a 92a 125a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 59 64a 81a 82a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 90 100 99 96 12 Mobile broadband subscriptions (per 100 people) 0.0 20.8a 14.3a 22.6a 10 Mobile broadband (% of total mobile subscriptions) 0.01 17.1a 15.4a 18.0a 8 Usage 6 Households with a mobile telephone (%) 30 76 84 82 Mobile voice usage (minutes per user per month) 450 347a 325a 288a 4 Population using mobile Internet (%) — — 22.9a 8.5 2 Short Message Service (SMS) users (% of mobile users) — 42.0 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Belarus Mobile basket (% of GNI per capita) 2.3 1.6 2.9 3.1 Europe & Central Asia Region Belgium High-income Belgium group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 10 11 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 36,600 45,840 38,746 150 Rural population (% of total) 3 3 22 120 Expected years of schooling (years) 16 16 16 Physicians density (per 1,000 people) 4.2 3.0 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,457 2005 2007 2009 2011 Belgium Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 92 122a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 62 49a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 100 1.8 Mobile broadband subscriptions (per 100 people) 0.3 33.8a 69.6a 1.5 Mobile broadband (% of total mobile subscriptions) 0.3 27.4a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 85 91 93 0.6 Mobile voice usage (minutes per user per month) 153 147a 339 0.3 Population using mobile Internet (%) — 7.7 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Belgium Mobile basket (% of GNI per capita) 1.6 1.1 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 146 Information and Communications for Development 2012 World Bank • Mobile at a Glance Benin Low-income Sub-Saharan Benin group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 8 9 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 570 780 530 1,188 150 Rural population (% of total) 60 58 72 63 Expected years of schooling (years) 9 — 9 9 120 Physicians density (per 1,000 people) 0.04 0.1 0.2 0.2 90 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,536 2005 2007 2009 2011 Benin Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 8 80 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 98 99a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 43 90 — 72 60 Mobile broadband subscriptions (per 100 people) — — — 5.6a 50 Mobile broadband (% of total mobile subscriptions) — — — 10.1a 40 Usage 30 Households with a mobile telephone (%) 24 — 43 52 Mobile voice usage (minutes per user per month) — 33 — — 20 Population using mobile Internet (%) — — — — 10 Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Benin Mobile basket (% of GNI per capita) 47.1 20.0 28.8 19.5 Sub-Saharan Africa Region Bolivia Latin America & Lower-middle- the Caribbean Bolivia income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 9 10 2,519 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,030 1,810 1,623 7,741 150 Rural population (% of total) 36 34 61 21 Expected years of schooling (years) 14 — 10 14 120 Physicians density (per 1,000 people) — — 0.8 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,450 0 2005 2007 2009 2011 Bolivia Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 26 72 78a 109a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 90 91a 96a 81a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 46 — 86 98 18 Mobile broadband subscriptions (per 100 people) — 3.1a 7.3a 16.1a 15 Mobile broadband (% of total mobile subscriptions) — 4.0a 9.0a 15.2a 12 Usage 9 Households with a mobile telephone (%) 39 74 77 84 Mobile voice usage (minutes per user per month) — — 276a 141a 6 Population using mobile Internet (%) — — 2.9 4.4 3 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Bolivia Mobile basket (% of GNI per capita) 14.3 7.5 7.2 3.7 Latin America & the Caribbean Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 147 World Bank • Mobile at a Glance Bosnia and Herzegovina Europe & Upper-middle- Central Asia Bosnia and Herzegovina income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 4 4 2,452 405 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 3,000 4,770 5,886 7,272 150 Rural population (% of total) 54 51 43 36 Expected years of schooling (years) 13 14 13 13 120 Physicians density (per 1,000 people) 1.4 1.6 1.7 3.2 90 Depositors with commercial banks (per 1,000 adults) 573 914 — 894 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,013 2005 2007 2009 2011 Sector performance Bosnia and Herzegovina Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 42 87 92a 125a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 86 86a 81a 82a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 97 100 99 96 12 Mobile broadband subscriptions (per 100 people) — 20.1a 14.3a 22.6a 10 Mobile broadband (% of total mobile subscriptions) — 24.1a 15.4a 18.0a 8 Usage 6 Households with a mobile telephone (%) 53 82 84 82 4 Mobile voice usage (minutes per user per month) — — 325a 288a Population using mobile Internet (%) — 4.5 22.9a 8.5 2 Short Message Service (SMS) users (% of mobile users) — 64.0a 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Bosnia and Herzegovina Mobile basket (% of GNI per capita) 7.1 3.9 2.9 3.1 Europe & Central Asia Region Botswana Upper-middle- Sub-Saharan Botswana income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 2 2 2,452 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 5,070 6,740 5,886 1,188 150 Rural population (% of total) 43 39 43 63 120 Expected years of schooling (years) 12 — 13 9 Physicians density (per 1,000 people) 0.3 — 1.7 0.2 90 Depositors with commercial banks (per 1,000 adults) 345 496 — 167 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,079 2005 2007 2009 2011 Botswana Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 30 144a 92a 57a Mobile cellular subscriptions (% prepaid) 98 98a 81a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 99 99 72 60 Mobile broadband subscriptions (per 100 people) — 10.0a 14.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) — 6.8a 15.4a 10.1a 40 Usage 30 Households with a mobile telephone (%) — 62 84 52 20 Mobile voice usage (minutes per user per month) — — 325a — Population using mobile Internet (%) — — 22.9a — 10 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Botswana Mobile basket (% of GNI per capita) 3.4 2.4 2.9 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 148 Information and Communications for Development 2012 World Bank • Mobile at a Glance Brazil Latin America & Upper-middle- the Caribbean Brazil income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 186 195 2,452 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 3,960 9,390 5,886 7,741 150 Rural population (% of total) 16 14 43 21 Expected years of schooling (years) 14 14 13 14 120 Physicians density (per 1,000 people) 1.7 1.8 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 4 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,537 0 2005 2007 2009 2011 Brazil Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 46 123a 92a 109a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 81 80a 81a 81a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 88 100 99 98 15 Mobile broadband subscriptions (per 100 people) 0.2 20.9a 14.3a 16.1a Mobile broadband (% of total mobile subscriptions) 0.3 16.7a 15.4a 15.2a 12 Usage 9 Households with a mobile telephone (%) 59 92 84 84 6 Mobile voice usage (minutes per user per month) 88 118a 325a 141a Population using mobile Internet (%) 1.5 2.7 22.9a 4.4 3 Short Message Service (SMS) users (% of mobile users) — 49.0 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Brazil Mobile basket (% of GNI per capita) 11.7 7.3 2.9 3.7 Latin America & the Caribbean Region Bulgaria Europe & Upper-middle- Central Asia Bulgaria income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 8 8 2,452 405 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 3,640 6,280 5,886 7,272 180 Rural population (% of total) 30 28 43 36 150 Expected years of schooling (years) 13 14 13 13 120 Physicians density (per 1,000 people) 3.7 3.7 1.7 3.2 Depositors with commercial banks (per 1,000 adults) 1,466 1,958 — 894 90 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,866 2005 2007 2009 2011 Bulgaria Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 81 151a 92a 125a Mobile cellular subscriptions (% prepaid) 67 39a 81a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 99 96 12 Mobile broadband subscriptions (per 100 people) 0.3 40.8a 14.3a 22.6a Mobile broadband (% of total mobile subscriptions) 0.4 25.8a 15.4a 18.0a 9 Usage 6 Households with a mobile telephone (%) 64 80 84 82 Mobile voice usage (minutes per user per month) — 118a 325a 288a 3 Population using mobile Internet (%) — — 22.9a 8.5 Short Message Service (SMS) users (% of mobile users) — — 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Bulgaria Mobile basket (% of GNI per capita) 10.1 5.9 2.9 3.1 Europe & Central Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 149 World Bank • Mobile at a Glance Burkina Faso Low-income Sub-Saharan Burkina Faso group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 14 16 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 390 550 530 1,188 150 Rural population (% of total) 82 80 72 63 120 Expected years of schooling (years) 5 6 9 9 Physicians density (per 1,000 people) 0.1 0.1 0.2 0.2 90 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,047 2005 2007 2009 2011 Burkina Faso Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 4 43a 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 99a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 26 — — 72 80 Mobile broadband subscriptions (per 100 people) — — — 5.6a Mobile broadband (% of total mobile subscriptions) — — — 10.1a 60 Usage 40 Households with a mobile telephone (%) 18 — 43 52 Mobile voice usage (minutes per user per month) — — — — 20 Population using mobile Internet (%) — — — — Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Burkina Faso Mobile basket (% of GNI per capita) 72.8 46.3 28.8 19.5 Sub-Saharan Africa Region Burundi Low-income Sub-Saharan Burundi group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 7 8 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 100 170 530 1,188 120 Rural population (% of total) 91 89 72 63 Expected years of schooling (years) 6 10 9 9 90 Physicians density (per 1,000 people) 0.03 — 0.2 0.2 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 Burundi Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 2 25a 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 100a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 82 83 — 72 60 Mobile broadband subscriptions (per 100 people) — 0.1a — 5.6a 50 Mobile broadband (% of total mobile subscriptions) — 0.4a — 10.1a 40 Usage 30 Households with a mobile telephone (%) — 32 43 52 20 Mobile voice usage (minutes per user per month) — — — — Population using mobile Internet (%) — 0.6 — — 10 Short Message Service (SMS) users (% of mobile users) — 25.0 — — 0 2005 2006 2007 2008 2009 2010 Affordability Burundi (—) Mobile basket (% of GNI per capita) — — 28.8 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 150 Information and Communications for Development 2012 World Bank • Mobile at a Glance Cambodia Low-income East Asia & Cambodia group Pacific Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 13 14 796 1,962 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 460 750 530 3,696 150 Rural population (% of total) 80 77 72 54 Expected years of schooling (years) 10 — 9 12 120 Physicians density (per 1,000 people) — 0.2 0.2 1.2 90 Depositors with commercial banks (per 1,000 adults) — 108 — — 60 Sector structure 30 Number of mobile operators — 7 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,354 2005 2007 2009 2011 Cambodia Sector performance East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 8 53 43a 83a Mobile cellular subscriptions (% prepaid) 94 98a 98a 85a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 75 99 — 99 20 Mobile broadband subscriptions (per 100 people) 0.04 9.1a — 11.6a Mobile broadband (% of total mobile subscriptions) 0.37 8.4a — 14.4a 15 Usage 10 Households with a mobile telephone (%) 20 62 43 83 Mobile voice usage (minutes per user per month) — — — 367a 5 Population using mobile Internet (%) — 2.8 — 22.4a Short Message Service (SMS) users (% of mobile users) — 26.1 — 84.0a 0 2005 2006 2007 2008 2009 2010 Affordability Cambodia Mobile basket (% of GNI per capita) 17.9 10.7 28.8 5.7 East Asia & Pacific Region Cameroon Lower-middle- Sub-Saharan Cameroon income group Africa Region 2005 2010 2010 2010 Economic and social context Population (total, million) 18 20 2,519 853 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 930 1,200 1,623 1,188 150 Rural population (% of total) 46 42 61 63 120 Expected years of schooling (years) 9 10 10 9 Physicians density (per 1,000 people) 0.2 — 0.8 0.2 90 Depositors with commercial banks (per 1,000 adults) 36 72 — 167 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,949 2005 2007 2009 2011 Cameroon Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 13 53a 78a 57a Mobile cellular subscriptions (% prepaid) 98 100a 96a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 54 — 86 72 60 Mobile broadband subscriptions (per 100 people) — — 7.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) — — 9.0a 10.1a 40 Usage 30 Households with a mobile telephone (%) 27 43 77 52 20 Mobile voice usage (minutes per user per month) — 42a 276a — Population using mobile Internet (%) — 1.3 2.9 — 10 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Cameroon Mobile basket (% of GNI per capita) 40.0 20.1 7.2 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 151 World Bank • Mobile at a Glance Canada High-income Canada group 2005 2010 2010 Economic and social context Population (total, million) 32 34 1,127 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 33,110 43,250 38,746 150 Rural population (% of total) 20 19 22 Expected years of schooling (years) — — 16 120 Physicians density (per 1,000 people) 1.9 2.0 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,019 0 2005 2007 2009 2011 Sector performance Canada High-income group Access Mobile cellular subscriptions (per 100 people) 53 74a 118a Mobile cellular subscriptions (% prepaid) 22 21a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 97 99 100 1.5 Mobile broadband subscriptions (per 100 people) 0.1 32.6a 69.6a Mobile broadband (% of total mobile subscriptions) 0.2 42.4a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 64 77 93 0.6 Mobile voice usage (minutes per user per month) 326 376a 339 Population using mobile Internet (%) 2.8 21.5a 24.3 0.3 Short Message Service (SMS) users (% of mobile users) — 67.4a 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability Canada Mobile basket (% of GNI per capita) 0.5 1.0 1.0 High-income group Central African Republic Central African Low-income Sub-Saharan Republic group Africa Region 2005 2010 2010 2010 Economic and social context Population (total, million) 4 4 796 853 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 340 470 530 1,188 100 Rural population (% of total) 62 61 72 63 Expected years of schooling (years) — 7 9 9 80 Physicians density (per 1,000 people) 0.1 — 0.2 0.2 60 Depositors with commercial banks (per 1,000 adults) 3 3 — 167 40 Sector structure 20 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 Central African Republic Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 2 17 43a 57a Mobile cellular subscriptions (% prepaid) 100 100a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 19 55 — 72 60 Mobile broadband subscriptions (per 100 people) — — — 5.6a 50 Mobile broadband (% of total mobile subscriptions) — — — 10.1a 40 Usage 30 Households with a mobile telephone (%) — 16 43 52 20 Mobile voice usage (minutes per user per month) — — — — 10 Population using mobile Internet (%) — — — — Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Central African Republic Mobile basket (% of GNI per capita) — 34.5 28.8 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 152 Information and Communications for Development 2012 World Bank • Mobile at a Glance Chad Low-income Sub-Saharan Chad group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 10 11 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 430 620 530 1,188 80 Rural population (% of total) 75 72 72 63 Expected years of schooling (years) 6 7 9 9 60 Physicians density (per 1,000 people) 0.04 — 0.2 0.2 Depositors with commercial banks (per 1,000 adults) 7 24 — 167 40 Sector structure 20 Number of mobile operators — 2 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,095 0 2005 2007 2009 2011 Chad Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 2 34a 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 100 100a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 24 — — 72 70 Mobile broadband subscriptions (per 100 people) — — — 5.6a 60 Mobile broadband (% of total mobile subscriptions) — — — 10.1a 50 Usage 40 Households with a mobile telephone (%) — 32 43 52 30 Mobile voice usage (minutes per user per month) — — — — 20 Population using mobile Internet (%) — — — — 10 Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Chad Mobile basket (% of GNI per capita) 57.7 29.8 28.8 19.5 Sub-Saharan Africa Region Chile Latin America & Upper-middle- the Caribbean Chile income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 16 17 2,452 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 5,920 10,120 5,886 7,741 150 Rural population (% of total) 12 11 43 21 Expected years of schooling (years) 14 15 13 14 120 Physicians density (per 1,000 people) 1.3 1.0 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) 1,425 2,134 — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,509 2005 2007 2009 2011 Chile Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 65 124a 92a 109a Mobile cellular subscriptions (% prepaid) 83 72a 81a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 99 98 8 Mobile broadband subscriptions (per 100 people) 0.0 13.1a 14.3a 16.1a Mobile broadband (% of total mobile subscriptions) 0.0 9.2a 15.4a 15.2a 6 Usage 4 Households with a mobile telephone (%) 61 91 84 84 Mobile voice usage (minutes per user per month) 131 169a 325a 141a 2 Population using mobile Internet (%) — 5.3 22.9a 4.4 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Chile Mobile basket (% of GNI per capita) 5.5 2.8 2.9 3.7 Latin America & the Caribbean Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 153 World Bank • Mobile at a Glance China Upper-middle- East Asia & China income group Pacific Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 1,304 1,338 2,452 1,962 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,740 4,270 5,886 3,696 150 Rural population (% of total) 60 55 43 54 120 Expected years of schooling (years) 11 12 13 12 Physicians density (per 1,000 people) 1.5 1.4 1.7 1.2 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,323 2005 2007 2009 2011 China Sector performance East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 30 73a 92a 83a Mobile cellular subscriptions (% prepaid) 71 81a 81a 85a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 95 99 99 99 8 Mobile broadband subscriptions (per 100 people) — 9.5a 14.3a 11.6a Mobile broadband (% of total mobile subscriptions) — 13.1a 15.4a 14.4a 6 Usage 4 Households with a mobile telephone (%) 55 93 84 83 Mobile voice usage (minutes per user per month) 299 450a 325a 367a 2 Population using mobile Internet (%) 0.5 26.5a 22.9a 22.4a 0 Short Message Service (SMS) users (% of mobile users) — 80.0a 74.4a 84.0a 2005 2006 2007 2008 2009 2010 Affordability China Mobile basket (% of GNI per capita) 3.4 1.7 2.9 5.7 East Asia & Pacific Region Colombia Latin America & Upper-middle- the Caribbean Colombia income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 43 46 2,452 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,940 5,510 5,886 7,741 150 Rural population (% of total) 26 25 43 21 Expected years of schooling (years) 13 14 13 14 120 Physicians density (per 1,000 people) 1.4 0.1 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,973 2005 2007 2009 2011 Colombia Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 51 102a 92a 109a Mobile cellular subscriptions (% prepaid) 83 81a 81a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 82 — 99 98 8 Mobile broadband subscriptions (per 100 people) — 9.0a 14.3a 16.1a Mobile broadband (% of total mobile subscriptions) — 9.4a 15.4a 15.2a 6 Usage 4 Households with a mobile telephone (%) 56 91 84 84 Mobile voice usage (minutes per user per month) 116 191a 325a 141a 2 Population using mobile Internet (%) — — 22.9a 4.4 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Colombia Mobile basket (% of GNI per capita) 6.4 3.7 2.9 3.7 Latin America & the Caribbean Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 154 Information and Communications for Development 2012 World Bank • Mobile at a Glance Congo, Dem. Rep. Low-income Sub-Saharan Congo, Dem. Rep. group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 57 66 796 853 Number per 100 prople GNI per capita, World Bank Atlas method (current US$) 120 180 530 1,188 150 Rural population (% of total) 68 65 72 63 120 Expected years of schooling (years) 8 8 9 9 90 Physicians density (per 1,000 people) 0.1 — 0.2 0.2 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,242 2005 2007 2009 2011 Congo, Dem. Rep. Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 5 14 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 99a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 50 50 — 72 60 Mobile broadband subscriptions (per 100 people) — — — 5.6a 50 Mobile broadband (% of total mobile subscriptions) — — — 10.1a 40 Usage 30 Households with a mobile telephone (%) 21 — 43 52 Mobile voice usage (minutes per user per month) — — — — 20 Population using mobile Internet (%) — — — — 10 Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Congo, Dem. Rep. (—) Mobile basket (% of GNI per capita) — — 28.8 19.5 Sub-Saharan Africa Region Congo, Rep. Lower-middle- Sub-Saharan Congo, Rep. income group Africa Region 2005 2010 2010 2010 Economic and social context Population (total, million) 4 4 2,519 853 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 980 2,240 1,623 1,188 150 Rural population (% of total) 40 38 61 63 120 Expected years of schooling (years) 10 — 10 9 Physicians density (per 1,000 people) 0.2 — 0.8 0.2 90 Depositors with commercial banks (per 1,000 adults) 5 20 — 167 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,078 2005 2007 2009 2011 Congo, Rep. Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 16 94a 78a 57a Mobile cellular subscriptions (% prepaid) 99 99a 96a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 39 — 86 72 60 Mobile broadband subscriptions (per 100 people) — 0.6a 7.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) — 0.6a 9.0a 10.1a 40 Usage 30 Households with a mobile telephone (%) 34 77 77 52 20 Mobile voice usage (minutes per user per month) — 50a 276a — Population using mobile Internet (%) — — 2.9 — 10 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Congo, Rep. (—) Mobile basket (% of GNI per capita) — — 7.2 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 155 World Bank • Mobile at a Glance Costa Rica Latin America & Upper-middle- the Caribbean Costa Rica income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 4 5 2,452 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 4,680 6,810 5,886 7,741 150 Rural population (% of total) 38 36 43 21 Expected years of schooling (years) 12 — 13 14 120 Physicians density (per 1,000 people) — — 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 1 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 10,000 2005 2007 2009 2011 Costa Rica Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 26 85a 92a 109a Mobile cellular subscriptions (% prepaid) — 52a 81a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 86 — 99 98 8 Mobile broadband subscriptions (per 100 people) — 16.5a 14.3a 16.1a Mobile broadband (% of total mobile subscriptions) — 19.3a 15.4a 15.2a 6 Usage 4 Households with a mobile telephone (%) 50 74 84 84 Mobile voice usage (minutes per user per month) 305 — 325a 141a 2 Population using mobile Internet (%) — 6.4 22.9a 4.4 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Costa Rica Mobile basket (% of GNI per capita) 1.6 0.6 2.9 3.7 Latin America & the Caribbean Region Côte d’Ivoire Lower-middle- Sub-Saharan Côte d’Ivoire income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 18 20 2,519 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 870 1,160 1,623 1,188 150 Rural population (% of total) 53 50 61 63 120 Expected years of schooling (years) — — 10 9 Physicians density (per 1,000 people) 0.1 0.1 0.8 0.2 90 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,849 2005 2007 2009 2011 Côte d'Ivoire Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 13 85a 78a 57a Mobile cellular subscriptions (% prepaid) 98 99a 96a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 55 92 86 72 80 Mobile broadband subscriptions (per 100 people) — — 7.3a 5.6a Mobile broadband (% of total mobile subscriptions) — — 9.0a 10.1a 60 Usage 40 Households with a mobile telephone (%) 23 — 77 52 Mobile voice usage (minutes per user per month) — — 276a — 20 Population using mobile Internet (%) — — 2.9 — Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Côte d'Ivoire Mobile basket (% of GNI per capita) 62.1 14.1 7.2 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 156 Information and Communications for Development 2012 World Bank • Mobile at a Glance Croatia High-income Croatia group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 4 4 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 9,730 13,890 38,746 150 Rural population (% of total) 44 42 22 Expected years of schooling (years) 14 14 16 120 Physicians density (per 1,000 people) 2.5 2.6 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,046 2005 2007 2009 2011 Croatia Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 82 117a 118a Mobile cellular subscriptions (% prepaid) 81 61a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 3.0 Mobile broadband subscriptions (per 100 people) 2.0 33.9a 69.6a 2.5 Mobile broadband (% of total mobile subscriptions) 2.4 29.0a 57.6a 2.0 Usage 1.5 Households with a mobile telephone (%) 79 95 93 1.0 Mobile voice usage (minutes per user per month) — 114a 339 Population using mobile Internet (%) 0.7 13.6 24.3 0.5 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability Croatia Mobile basket (% of GNI per capita) 2.8 1.5 1.0 High-income group Cuba Latin America & Upper-middle- the Caribbean Cuba income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 11 11 2,452 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 3,960 5,460 5,886 7,741 150 Rural population (% of total) 24 24 43 21 Expected years of schooling (years) 15 18 13 14 120 Physicians density (per 1,000 people) 6.4 6.7 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 1 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 10,000 2005 2007 2009 2011 Cuba Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 1 9 92a 109a Mobile cellular subscriptions (% prepaid) 87 90a 81a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 71 78 99 98 8 Mobile broadband subscriptions (per 100 people) — — 14.3a 16.1a Mobile broadband (% of total mobile subscriptions) — — 15.4a 15.2a 6 Usage 4 Households with a mobile telephone (%) 1 — 84 84 Mobile voice usage (minutes per user per month) — — 325a 141a 2 Population using mobile Internet (%) — — 22.9a 4.4 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Cuba (—) Mobile basket (% of GNI per capita) — — 2.9 3.7 Latin America & the Caribbean Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 157 World Bank • Mobile at a Glance Cyprus High-income Cyprus group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 1 1 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 21,490 29,430 38,746 150 Rural population (% of total) 31 30 22 Expected years of schooling (years) 14 15 16 120 Physicians density (per 1,000 people) 2.3 2.6 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 6,429 2005 2007 2009 2011 Cyprus Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 76 84a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 56 59a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 1.5 Mobile broadband subscriptions (per 100 people) 0.6 58.6a 69.6a Mobile broadband (% of total mobile subscriptions) 0.6 42.0a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 85 — 93 0.6 Mobile voice usage (minutes per user per month) — — 339 0.3 Population using mobile Internet (%) — 3.6 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Cyprus Mobile basket (% of GNI per capita) 1.2 0.3 1.0 High-income group Czech Republic High-income Czech Republic group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 10 11 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 11,330 17,890 38,746 150 Rural population (% of total) 27 27 22 120 Expected years of schooling (years) 15 16 16 Physicians density (per 1,000 people) 3.6 3.7 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,489 2005 2007 2009 2011 Czech Republic Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 115 129a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 66 43a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 4 Mobile broadband subscriptions (per 100 people) 0.7 34.7a 69.6a Mobile broadband (% of total mobile subscriptions) 0.7 26.6a 57.6a 3 Usage 2 Households with a mobile telephone (%) 81 95 93 Mobile voice usage (minutes per user per month) 194 141a 339 1 Population using mobile Internet (%) — 4.8 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Czech Republic Mobile basket (% of GNI per capita) 3.3 1.9 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 158 Information and Communications for Development 2012 World Bank • Mobile at a Glance Denmark High-income Denmark group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 5 6 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 48,590 59,400 38,746 150 Rural population (% of total) 14 13 22 Expected years of schooling (years) 17 17 16 120 Physicians density (per 1,000 people) 3.2 3.4 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,401 2005 2007 2009 2011 Denmark Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 101 141a 118a Mobile cellular subscriptions (% prepaid) 23 15a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) — — 100 1.5 Mobile broadband subscriptions (per 100 people) 2.3 84.4a 69.6a Mobile broadband (% of total mobile subscriptions) 2.1 55.5a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 91 97 93 0.6 Mobile voice usage (minutes per user per month) 159 173a 339 0.3 Population using mobile Internet (%) 8.6 21.6 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Denmark Mobile basket (% of GNI per capita) 0.9 0.2 1.0 High-income group Dominican Republic Latin America & Dominican Upper-middle- the Caribbean Republic income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 9 10 2,452 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,900 5,030 5,886 7,741 150 Rural population (% of total) 33 30 43 21 Expected years of schooling (years) 12 — 13 14 120 Physicians density (per 1,000 people) — — 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,085 2005 2007 2009 2011 Dominican Republic Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 39 86a 92a 109a Mobile cellular subscriptions (% prepaid) 87 85a 81a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) — 81 99 98 8 Mobile broadband subscriptions (per 100 people) 0.05 4.5a 14.3a 16.1a Mobile broadband (% of total mobile subscriptions) 0.12 4.8a 15.4a 15.2a 6 Usage 4 Households with a mobile telephone (%) 44 — 84 84 Mobile voice usage (minutes per user per month) — — 325a 141a 2 Population using mobile Internet (%) — — 22.9a 4.4 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Dominican Republic Mobile basket (% of GNI per capita) 5.6 3.7 2.9 3.7 Latin America & the Caribbean Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 159 World Bank • Mobile at a Glance Ecuador Latin America & Upper-middle- the Caribbean Ecuador income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 13 14 2,452 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,620 3,850 5,886 7,741 150 Rural population (% of total) 36 33 43 21 Expected years of schooling (years) 13 14 13 14 120 Physicians density (per 1,000 people) — 1.7 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,625 2005 2007 2009 2011 Ecuador Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 47 107a 92a 109a Mobile cellular subscriptions (% prepaid) 87 84a 81a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 80 93 99 98 14 Mobile broadband subscriptions (per 100 people) 0.03 9.0a 14.3a 16.1a 12 Mobile broadband (% of total mobile subscriptions) 0.07 8.3a 15.4a 15.2a 10 Usage 8 Households with a mobile telephone (%) 64 75 84 84 6 Mobile voice usage (minutes per user per month) 46 145a 325a 141a 4 Population using mobile Internet (%) — 2.4 22.9a 4.4 2 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Ecuador Mobile basket (% of GNI per capita) 10.8 4.3 2.9 3.7 Latin America & the Caribbean Region Egypt, Arab Rep. Middle East & Lower-middle- North Africa Egypt, Arab Rep. income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 74 81 2,519 331 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,250 2,420 1,623 3,874 150 Rural population (% of total) 57 57 61 42 Expected years of schooling (years) 11 — 10 12 120 Physicians density (per 1,000 people) 2.4 2.8 0.8 1.4 90 Depositors with commercial banks (per 1,000 adults) — — — 443 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,003 2005 2007 2009 2011 Egypt, Arab Rep. Sector performance Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 17 97a 78a 89a Mobile cellular subscriptions (% prepaid) 88 96a 96a 87a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 92 100 86 — 12 Mobile broadband subscriptions (per 100 people) — 11.6a 7.3a — 10 Mobile broadband (% of total mobile subscriptions) — 11.4a 9.0a — 8 Usage 6 Households with a mobile telephone (%) 25 79 77 — 4 Mobile voice usage (minutes per user per month) 128 178a 276a — Population using mobile Internet (%) — 6.4 2.9 4.5 2 Short Message Service (SMS) users (% of mobile users) — 72.0a 61.9a — 0 2005 2006 2007 2018 2019 2010 Affordability Egypt, Arab Rep. Mobile basket (% of GNI per capita) 10.7 3.5 7.2 3.6 Middle East & North Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 160 Information and Communications for Development 2012 World Bank • Mobile at a Glance El Salvador Latin America & Lower-middle- the Caribbean El Salvador income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 6 6 2,519 583 Mobile cellular subscriptions, 2005–11 GNI per capita, World Bank Atlas method (current US$) 2,820 3,380 1,623 7,741 Number per 100 people 150 Rural population (% of total) 40 39 61 21 Expected years of schooling (years) 12 12 10 14 120 Physicians density (per 1,000 people) 1.5 1.6 0.8 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 El Salvador Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 40 126 78a 109a Mobile cellular subscriptions (% prepaid) 83 89a 96a 81a Mobile basket, 2005–10 Population covered by a mobile-cellular network (%) 95 — 86 98 Percentage of GNI per capita Mobile broadband subscriptions (per 100 people) — 7.0a 7.3a 16.1a 8 Mobile broadband (% of total mobile subscriptions) — 5.0a 9.0a 15.2a 6 Usage Households with a mobile telephone (%) 35 87 77 84 4 Mobile voice usage (minutes per user per month) — — 276a 141a 2 Population using mobile Internet (%) — — 2.9 4.4 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability El Salvador Mobile basket (% of GNI per capita) 5.1 3.4 7.2 3.7 Latin America & the Caribbean Region Eritrea Low-income Sub-Saharan Eritrea group Africa Region 2005 2010 2010 2010 Economic and social context Population (total, million) 4 5 796 853 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 250 340 530 1,188 100 Rural population (% of total) 81 78 72 63 80 Expected years of schooling (years) 6 5 9 9 Physicians density (per 1,000 people) 0.1 — 0.2 0.2 60 Depositors with commercial banks (per 1,000 adults) — — — 167 40 Sector structure 20 Number of mobile operators — 1 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 10,000 2005 2007 2009 2011 Eritrea Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 1 4 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 99a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 1.3 90 — 72 60 Mobile broadband subscriptions (per 100 people) — — — 5.6a 50 Mobile broadband (% of total mobile subscriptions) — — — 10.1a 40 Usage 30 Households with a mobile telephone (%) — — 43 52 20 Mobile voice usage (minutes per user per month) — — — — Population using mobile Internet (%) — — — — 10 Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Eritrea (—) Mobile basket (% of GNI per capita) — — 28.8 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 161 World Bank • Mobile at a Glance Estonia High-income Estonia group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 1 1 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 9,760 14,460 38,746 150 Rural population (% of total) 31 31 22 120 Expected years of schooling (years) 16 16 16 Physicians density (per 1,000 people) 3.3 3.3 2.8 90 Depositors with commercial banks (per 1,000 adults) — 1,993 — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,674 2005 2007 2009 2011 Estonia Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 107 135a 118a Mobile cellular subscriptions (% prepaid) 56 55a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 100 3.5 Mobile broadband subscriptions (per 100 people) 0.05 12.8a 69.6a 3.0 Mobile broadband (% of total mobile subscriptions) 0.05 9.5a 57.6a 2.5 Usage 2.0 Households with a mobile telephone (%) 81 91 93 1.5 Mobile voice usage (minutes per user per month) — — 339 1.0 Population using mobile Internet (%) 3.7 3.0 24.3 0.5 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability Estonia Mobile basket (% of GNI per capita) 2.9 1.9 1.0 High-income group Ethiopia Low-income Sub-Saharan Ethiopia group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 74 83 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 160 390 530 1,188 150 Rural population (% of total) 84 82 72 63 120 Expected years of schooling (years) 7 9 9 9 Physicians density (per 1,000 people) 0.02 — 0.2 0.2 90 Depositors with commercial banks (per 1,000 adults) 66 107 — 167 60 Sector structure 30 Number of mobile operators — 1 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 10,000 2005 2007 2009 2011 Ethiopia Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 1 12a 43a 57a Mobile cellular subscriptions (% prepaid) 92 99a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 10 — — 72 60 Mobile broadband subscriptions (per 100 people) — 1.1a — 5.6a 50 Mobile broadband (% of total mobile subscriptions) — 6.7a — 10.1a 40 Usage 30 Households with a mobile telephone (%) 2 25 43 52 20 Mobile voice usage (minutes per user per month) — — — — Population using mobile Internet (%) — — — — 10 Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Ethiopia Mobile basket (% of GNI per capita) 40.2 12.6 28.8 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 162 Information and Communications for Development 2012 World Bank • Mobile at a Glance Finland High-income Finland group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 5 5 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 38,550 47,570 38,746 180 Rural population (% of total) 38 36 22 150 Expected years of schooling (years) 17 17 16 120 Physicians density (per 1,000 people) 3.3 2.9 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,350 2005 2007 2009 2011 Finland Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 100 163a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 6 9a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 100 1.5 Mobile broadband subscriptions (per 100 people) 1.1 96.4a 69.6a 1.2 Mobile broadband (% of total mobile subscriptions) 1.0 55.2a 57.6a 0.9 Usage Households with a mobile telephone (%) 96 99 93 0.6 Mobile voice usage (minutes per user per month) 236 206a 339 0.3 Population using mobile Internet (%) 9.5 24.2 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Finland Mobile basket (% of GNI per capita) 0.5 0.3 1.0 High-income group France High-income France group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 63 65 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 34,890 42,370 38,746 150 Rural population (% of total) 23 22 22 120 Expected years of schooling (years) 16 16 16 Physicians density (per 1,000 people) 3.4 3.4 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,223 2005 2007 2009 2011 France Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 76 98a 118a Mobile cellular subscriptions (% prepaid) 36 30a 36a Mobile basket, 2005–10 Population covered by a mobile-cellular network (%) 99 99 100 Percentage of GNI per capita 1.8 Mobile broadband subscriptions (per 100 people) 2.1 41.3a 69.6a Mobile broadband (% of total mobile subscriptions) 2.9 42.3a 57.6a 1.5 1.2 Usage 0.9 Households with a mobile telephone (%) 81 88 93 Mobile voice usage (minutes per user per month) 233 218a 339 0.6 Population using mobile Internet (%) 4.4 18.9a 24.3 0.3 Short Message Service (SMS) users (% of mobile users) — 81.8 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability France Mobile basket (% of GNI per capita) 1.7 1.4 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 163 World Bank • Mobile at a Glance Gabon Upper-middle- Sub-Saharan Gabon income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 1 2 2,452 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 5,110 7,650 5,886 1,188 180 Rural population (% of total) 16 14 43 63 150 Expected years of schooling (years) — — 13 9 120 Physicians density (per 1,000 people) 0.3 — 1.7 0.2 Depositors with commercial banks (per 1,000 adults) 43 95 — 167 90 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,584 2005 2007 2009 2011 Gabon Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 54 165a 92a 57a Mobile cellular subscriptions (% prepaid) 99 99a 81a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 78 — 99 72 60 Mobile broadband subscriptions (per 100 people) — — 14.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) — — 15.4a 10.1a 40 Usage 30 Households with a mobile telephone (%) — — 84 52 20 Mobile voice usage (minutes per user per month) — — 325a — 10 Population using mobile Internet (%) — — 22.9a — Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Gabon (—) Mobile basket (% of GNI per capita) — — 2.9 19.5 Sub-Saharan Africa Region Gambia, The Low-income Sub-Saharan Gambia, The group Africa Region 2005 2010 2010 2010 Economic and social context Population (total, million) 2 2 796 853 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 270 450 530 1,188 150 Rural population (% of total) 46 42 72 63 Expected years of schooling (years) — 9 9 9 120 Physicians density (per 1,000 people) 0.1 0.0 0.2 0.2 90 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 Gambia, The Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 16 86 43a 57a Mobile cellular subscriptions (% prepaid) 99 100a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 70 — — 72 60 Mobile broadband subscriptions (per 100 people) — 1.5a — 5.6a 50 Mobile broadband (% of total mobile subscriptions) — 1.3a — 10.1a 40 Usage 30 Households with a mobile telephone (%) — — 43 52 20 Mobile voice usage (minutes per user per month) 51 — — — 10 Population using mobile Internet (%) — — — — Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Gambia, The (—) Mobile basket (% of GNI per capita) — 17.1 28.8 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 164 Information and Communications for Development 2012 World Bank • Mobile at a Glance Georgia Europe & Lower-middle- Central Asia Georgia income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 4 4 2,519 405 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,360 2,690 1,623 7,272 150 Rural population (% of total) 48 47 61 36 120 Expected years of schooling (years) 13 13 10 13 Physicians density (per 1,000 people) 4.7 4.8 0.8 3.2 90 Depositors with commercial banks (per 1,000 adults) 363 697 — 894 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,465 2005 2007 2009 2011 Georgia Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 27 111a 78a 125a Mobile cellular subscriptions (% prepaid) 88 89a 96a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 95 99 86 96 12 Mobile broadband subscriptions (per 100 people) 0.4 17.2a 7.3a 22.6a 10 Mobile broadband (% of total mobile subscriptions) 1.0 15.0a 9.0a 18.0a 8 Usage 6 Households with a mobile telephone (%) 30 80 77 82 4 Mobile voice usage (minutes per user per month) 91 148a 276a 288a Population using mobile Internet (%) — — 2.9 8.5 2 Short Message Service (SMS) users (% of mobile users) — 38.0 61.9a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Georgia Mobile basket (% of GNI per capita) 10.1 5.2 7.2 3.1 Europe & Central Asia Region Germany High-income Germany group 2005 2010 2010 Economic and social context Population (total, million) 82 82 1,127 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 34,780 43,070 38,746 150 Rural population (% of total) 27 26 22 120 Expected years of schooling (years) — — 16 Physicians density (per 1,000 people) 3.4 3.6 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,749 2005 2007 2009 2011 Germany Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 96 140a 118a Mobile cellular subscriptions (% prepaid) 51 56a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 99 100 2.0 Mobile broadband subscriptions (per 100 people) 2.4 51.1a 69.6a Mobile broadband (% of total mobile subscriptions) 2.5 36.5a 57.6a 1.5 Usage 1.0 Households with a mobile telephone (%) 84 89 93 Mobile voice usage (minutes per user per month) 90 116a 339 0.5 Population using mobile Internet (%) 1.8 16.4a 24.3 0 Short Message Service (SMS) users (% of mobile users) 76.2 79.8 78.2a 2005 2006 2007 2008 2009 2010 Affordability Germany Mobile basket (% of GNI per capita) 1.8 0.4 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 165 World Bank • Mobile at a Glance Ghana Lower-middle- Sub-Saharan Ghana income group Africa Region 2005 2010 2010 2010 Economic and social context Population (total, million) 22 24 2,519 853 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 460 1,250 1,623 1,188 150 Rural population (% of total) 52 49 61 63 Expected years of schooling (years) 9 10 10 9 120 Physicians density (per 1,000 people) 0.2 0.1 0.8 0.2 90 Depositors with commercial banks (per 1,000 adults) 173 324 — 167 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,374 2005 2007 2009 2011 Ghana Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 13 85a 78a 57a Mobile cellular subscriptions (% prepaid) 99 102a 96a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 59 77 86 72 60 Mobile broadband subscriptions (per 100 people) — 1.7a 7.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) — 2.0a 9.0a 10.1a 40 Usage 30 Households with a mobile telephone (%) 20 72 77 52 20 Mobile voice usage (minutes per user per month) 104 114 276a — Population using mobile Internet (%) — — 2.9 — 10 Short Message Service (SMS) users (% of mobile users) — 20.0 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Ghana Mobile basket (% of GNI per capita) 42.2 7.1 7.2 19.5 Sub-Saharan Africa Region Greece High-income Greece group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 11 11 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 21,400 26,950 38,746 150 Rural population (% of total) 40 39 22 120 Expected years of schooling (years) 17 — 16 Physicians density (per 1,000 people) 5.0 6.2 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,747 2005 2007 2009 2011 Greece Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 92 141a 118a Mobile cellular subscriptions (% prepaid) 67 69a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 2.5 Mobile broadband subscriptions (per 100 people) 2.1 60.0a 69.6a Mobile broadband (% of total mobile subscriptions) 1.8 43.7a 57.6a 2.0 Usage 1.5 Households with a mobile telephone (%) 76 93 93 1.0 Mobile voice usage (minutes per user per month) 138 245a 339 0.5 Population using mobile Internet (%) 0.9 1.7 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Greece Mobile basket (% of GNI per capita) 1.9 1.7 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 166 Information and Communications for Development 2012 World Bank • Mobile at a Glance Guatemala Latin America & Lower-middle- the Caribbean Guatemala income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 13 14 2,519 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,070 2,740 1,623 7,741 150 Rural population (% of total) 53 51 61 21 Expected years of schooling (years) 10 — 10 14 120 Physicians density (per 1,000 people) — — 0.8 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,481 2005 2007 2009 2011 Guatemala Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 35 126a 78a 109a Mobile cellular subscriptions (% prepaid) 94 95a 96a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 76 — 86 98 10 Mobile broadband subscriptions (per 100 people) 0.1 6.2a 7.3a 16.1a Mobile broadband (% of total mobile subscriptions) 0.3 6.4a 9.0a 15.2a 8 Usage 6 Households with a mobile telephone (%) 55 — 77 84 4 Mobile voice usage (minutes per user per month) — — 276a 141a 2 Population using mobile Internet (%) — — 2.9 4.4 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Guatemala Mobile basket (% of GNI per capita) 4.5 3.4 7.2 3.7 Latin America & the Caribbean Region Guinea Low-income Sub-Saharan Guinea group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 9 10 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 360 400 530 1,188 150 Rural population (% of total) 67 65 72 63 120 Expected years of schooling (years) 7 9 9 9 Physicians density (per 1,000 people) 0.1 — 0.2 0.2 90 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,699 2005 2007 2009 2011 Guinea Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 2 46a 43a 57a Mobile cellular subscriptions (% prepaid) 98 99a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 80 80 — 72 60 Mobile broadband subscriptions (per 100 people) — — — 5.6a 50 Mobile broadband (% of total mobile subscriptions) — — — 10.1a 40 Usage 30 Households with a mobile telephone (%) — — 43 52 20 Mobile voice usage (minutes per user per month) — — — — 10 Population using mobile Internet (%) — — — — Short Message Service (SMS) users (% of mobile users) — 17.0 — — 0 2005 2006 2007 2008 2009 2010 Affordability Guinea Mobile basket (% of GNI per capita) 25.4 12.3 28.8 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 167 World Bank • Mobile at a Glance Guinea-Bissau Low-income Sub-Saharan Guinea-Bissau group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 1 2 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 410 590 530 1,188 150 Rural population (% of total) 70 70 72 63 Expected years of schooling (years) 9 — 9 9 120 Physicians density (per 1,000 people) 0.12 0.05 0.2 0.2 90 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 6,250 2005 2007 2009 2011 Guinea-Bissau Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 7 56a 43a 57a Mobile cellular subscriptions (% prepaid) 98 99a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 65 — — 72 60 Mobile broadband subscriptions (per 100 people) — — — 5.6a 50 Mobile broadband (% of total mobile subscriptions) — — — 10.1a 40 Usage 30 Households with a mobile telephone (%) — — 43 52 20 Mobile voice usage (minutes per user per month) — 23a — — 10 Population using mobile Internet (%) — — — — Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Guinea-Bissau (—) Mobile basket (% of GNI per capita) — — 28.8 19.5 Sub-Saharan Africa Region Haiti Latin America & Low-income the Caribbean Haiti group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 9 10 796 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 400 670 530 7,741 150 Rural population (% of total) 57 50 72 21 Expected years of schooling (years) — — 9 14 120 Physicians density (per 1,000 people) — — 0.2 1.8 90 Depositors with commercial banks (per 1,000 adults) 233 339 — — 60 Sector structure 30 Number of mobile operators — — 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 Haiti Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 5 55a 43a 109a Mobile cellular subscriptions (% prepaid) 95 96a 98a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) — — — 98 8.0 Mobile broadband subscriptions (per 100 people) 0.3 3.0a — 16.1a Mobile broadband (% of total mobile subscriptions) 1.3 5.4a — 15.2a 6.0 Usage 4.0 Households with a mobile telephone (%) 17 — 43 84 Mobile voice usage (minutes per user per month) — — — 141a 2.0 Population using mobile Internet (%) — — — 4.4 Short Message Service (SMS) users (% of mobile users) — 73.0 — — 0.0 2005 2006 2007 2008 2009 2010 Affordability Haiti (—) Mobile basket (% of GNI per capita) — — 28.8 3.7 Latin America & the Caribbean Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 168 Information and Communications for Development 2012 World Bank • Mobile at a Glance Honduras Latin America & Lower-middle- the Caribbean Honduras income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 7 8 2,519 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,400 1,870 1,623 7,741 150 Rural population (% of total) 54 51 61 21 Expected years of schooling (years) — 11 10 14 120 Physicians density (per 1,000 people) — — 0.8 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,822 2005 2007 2009 2011 Honduras Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 19 103a 78a 109a Mobile cellular subscriptions (% prepaid) 92 93a 96a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 57 — 86 98 14 Mobile broadband subscriptions (per 100 people) — 6.2a 7.3a 16.1a 12 Mobile broadband (% of total mobile subscriptions) — 6.5a 9.0a 15.2a 10 Usage 8 Households with a mobile telephone (%) 41 81 77 84 6 Mobile voice usage (minutes per user per month) — — 276a 141a 4 Population using mobile Internet (%) — — 2.9 4.4 2 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Honduras Mobile basket (% of GNI per capita) 11.4 5.7 7.2 3.7 Latin America & the Caribbean Region Hong Kong SAR, China Hong Kong SAR, High-income China group 2005 2010 2010 Economic and social context Population (total, million) 7 7 1,127 GNI per capita, World Bank Atlas method (current US$) 28,150 32,780 38,746 Mobile cellular subscriptions, 2005–11 Number per 100 people Rural population (% of total) 0 0 22 200 Expected years of schooling (years) 14 16 16 Physicians density (per 1,000 people) — — 2.8 150 Depositors with commercial banks (per 1,000 adults) — — — 100 Sector structure Number of mobile operators — 5 50 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 0 2005 2007 2009 2011 Sector performance Hong Kong SAR, China Access High-income group Mobile cellular subscriptions (per 100 people) 114 183a 118a Mobile cellular subscriptions (% prepaid) 39 49a 36a Population covered by a mobile-cellular network (%) 100 100 100 Mobile basket, 2005–10 Percentage of GNI per capita Mobile broadband subscriptions (per 100 people) 9.3 89.5a 69.6a 1.5 Mobile broadband (% of total mobile subscriptions) 8.2 53.2a 57.6a 1.2 Usage Households with a mobile telephone (%) 88 98 93 0.9 Mobile voice usage (minutes per user per month) — — 339 0.6 Population using mobile Internet (%) 3.6 21.2 24.3 0.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a Affordability 0.0 2005 2006 2007 2008 2009 2010 Mobile basket (% of GNI per capita) 0.2 0.1 1.0 Hong Kong SAR, China High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 169 World Bank • Mobile at a Glance Hungary High-income Hungary group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 10 10 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 10,220 12,860 38,746 150 Rural population (% of total) 34 32 22 Expected years of schooling (years) 15 15 16 120 Physicians density (per 1,000 people) 3.0 3.0 2.8 90 Depositors with commercial banks (per 1,000 adults) 840 1,072 — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,555 2005 2007 2009 2011 Hungary Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 92 111a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 68 52a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 99 100 5 Mobile broadband subscriptions (per 100 people) 0.4 39.3a 69.6a 4 Mobile broadband (% of total mobile subscriptions) 0.5 36.1a 57.6a Usage 3 Households with a mobile telephone (%) 80 87 93 2 Mobile voice usage (minutes per user per month) 144 174a 339 1 Population using mobile Internet (%) 0.1 9.0 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Hungary Mobile basket (% of GNI per capita) 3.4 2.4 1.0 High-income group India Lower-middle- South Asia India income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 1,140 1,225 2,519 1,633 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 720 1,270 1,623 1,176 120 Rural population (% of total) 71 70 61 70 100 Expected years of schooling (years) 10 — 10 10 80 Physicians density (per 1,000 people) 0.6 0.6 0.8 0.6 Depositors with commercial banks (per 1,000 adults) 637 747 — 249 60 40 Sector structure 20 Number of mobile operators — 8 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 1,393 0 2005 2007 2009 2011 Sector performance India South Asia Region Access Mobile cellular subscriptions (per 100 people) 8 70a 78a 67a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 80 96a 96a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 31 83 86 84 12 Mobile broadband subscriptions (per 100 people) — 3.3a 7.3a 3.3a 10 Mobile broadband (% of total mobile subscriptions) — 4.6a 9.0a 4.6a 8 Usage 6 Households with a mobile telephone (%) 13 53 77 54 4 Mobile voice usage (minutes per user per month) 425 330a 276a 305a Population using mobile Internet (%) 0.1 3.3a 2.9 3.3a 2 Short Message Service (SMS) users (% of mobile users) — 49.0a 61.9a 47.0a 0 2005 2006 2007 2008 2009 2010 Affordability India Mobile basket (% of GNI per capita) 11.0 3.2 7.2 3.2 South Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 170 Information and Communications for Development 2012 World Bank • Mobile at a Glance Indonesia Lower-middle- East Asia & Indonesia income group Pacific Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 227 240 2,519 1,962 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,220 2,500 1,623 3,696 150 Rural population (% of total) 52 46 61 54 120 Expected years of schooling (years) 12 13 10 12 Physicians density (per 1,000 people) 0.1 — 0.8 1.2 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 5 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,229 0 2005 2007 2009 2011 Indonesia Sector performance East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 21 103a 78a 83a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 95 98a 96a 85a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 90 — 86 99 10 Mobile broadband subscriptions (per 100 people) 0.05 16.1a 7.3a 11.6a 8 Mobile broadband (% of total mobile subscriptions) 0.17 15.7a 9.0a 14.4a Usage 6 Households with a mobile telephone (%) 20 72 77 83 4 Mobile voice usage (minutes per user per month) 50 191a 276a 367a 2 Population using mobile Internet (%) 0.04 8.0a 2.9 22.4a Short Message Service (SMS) users (% of mobile users) — 96.0a 61.9a 84.0a 0 2005 2006 2007 2008 2009 2010 Affordability Indonesia Mobile basket (% of GNI per capita) 8.2 3.7 7.2 5.7 East Asia & Pacific Region Iran, Islamic Rep. Middle East & Upper-middle- North Africa Iran, Islamic Rep. income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 70 74 2,452 331 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,550 4,520 5,886 3,874 150 Rural population (% of total) 33 31 43 42 Expected years of schooling (years) 12 13 13 12 120 Physicians density (per 1,000 people) 0.9 — 1.7 1.4 90 Depositors with commercial banks (per 1,000 adults) — — — 443 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 0 2005 2007 2009 2011 Sector performance Iran, Islamic Rep. Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 12 103a 92a 89a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 3 64a 81a 87a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 75 — 99 — 10 Mobile broadband subscriptions (per 100 people) — — 14.3a — 8 Mobile broadband (% of total mobile subscriptions) — — 15.4a — Usage 6 Households with a mobile telephone (%) — 71 84 — 4 Mobile voice usage (minutes per user per month) — — 325a — 2 Population using mobile Internet (%) — 3.0 22.9a 4.5 Short Message Service (SMS) users (% of mobile users) — 56.0 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Iran, Islamic Rep. (—) Mobile basket (% of GNI per capita) — 0.9 2.9 3.6 Middle East & North Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 171 World Bank • Mobile at a Glance Iraq Middle East & Lower-middle- North Africa Iraq income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 28 32 2,519 331 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,150 2,340 1,623 3,874 150 Rural population (% of total) 33 34 61 42 Expected years of schooling (years) 10 — 10 12 120 Physicians density (per 1,000 people) 0.7 0.7 0.8 1.4 90 Depositors with commercial banks (per 1,000 adults) — — — 443 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,518 0 2005 2007 2009 2011 Sector performance Iraq Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 6 71a 78a 89a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 97 100a 96a 87a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 68 — 86 — 10 Mobile broadband subscriptions (per 100 people) — — 7.3a — 8 Mobile broadband (% of total mobile subscriptions) — — 9.0a — Usage 6 Households with a mobile telephone (%) — 94 77 — 4 Mobile voice usage (minutes per user per month) — — 276a — 2 Population using mobile Internet (%) — 5.0 2.9 4.5 Short Message Service (SMS) users (% of mobile users) — 62.0 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Iraq (—) Mobile basket (% of GNI per capita) — — 7.2 3.6 Middle East & North Africa Region Ireland High-income Ireland group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 4 4 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 42,380 41,820 38,746 150 Rural population (% of total) 40 38 22 120 Expected years of schooling (years) 18 18 16 Physicians density (per 1,000 people) 2.9 3.2 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 4 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,357 0 2005 2007 2009 2011 Sector performance Ireland High-income group Access Mobile cellular subscriptions (per 100 people) 100 122a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 76 62a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 99 100 10 Mobile broadband subscriptions (per 100 people) 4.4 53.6a 69.6a 8 Mobile broadband (% of total mobile subscriptions) 4.3 45.2a 57.6a 6 Usage Households with a mobile telephone (%) 89 92 93 4 Mobile voice usage (minutes per user per month) 217 245 339 2 Population using mobile Internet (%) 0.7 17.7a 24.3 Short Message Service (SMS) users (% of mobile users) — 71.0 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Ireland Mobile basket (% of GNI per capita) 1.1 1.1 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 172 Information and Communications for Development 2012 World Bank • Mobile at a Glance Israel High-income Israel group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 7 8 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 20,250 27,180 38,746 150 Rural population (% of total) 8 8 22 120 Expected years of schooling (years) 15 16 16 Physicians density (per 1,000 people) 3.7 3.7 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — — Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 0 2005 2007 2009 2011 Israel Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 112 128a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 22 22a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 100 1.8 Mobile broadband subscriptions (per 100 people) 5.5 65.8a 69.6a 1.5 Mobile broadband (% of total mobile subscriptions) 4.9 51.9a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 86 92 93 0.6 Mobile voice usage (minutes per user per month) 298 380a 339 Population using mobile Internet (%) — 17.1 24.3 0.3 Short Message Service (SMS) users (% of mobile users) — 73.0a 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Israel Mobile basket (% of GNI per capita) 1.1 1.5 1.0 High-income group Italy High-income Italy group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 59 60 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 30,880 35,700 38,746 180 Rural population (% of total) 32 32 22 150 Expected years of schooling (years) 16 16 16 120 Physicians density (per 1,000 people) 3.7 3.5 2.8 Depositors with commercial banks (per 1,000 adults) 749 1,307 — 90 60 Sector structure 30 Number of mobile operators — 4 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,011 0 2005 2007 2009 2011 Italy Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 122 153a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 90 82a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 10 Mobile broadband subscriptions (per 100 people) 17.6 69.5a 69.6a 8 Mobile broadband (% of total mobile subscriptions) 14.4 45.5a 57.6a Usage 6 Households with a mobile telephone (%) 88 93 93 4 Mobile voice usage (minutes per user per month) 117 161a 339 2 Population using mobile Internet (%) 1.7 15.9 24.3 Short Message Service (SMS) users (% of mobile users) — 77.7 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Italy Mobile basket (% of GNI per capita) 1.1 1.0 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 173 World Bank • Mobile at a Glance Jamaica Latin America & Upper-middle- the Caribbean Jamaica income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 3 3 2,452 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 3,910 4,800 5,886 7,741 150 Rural population (% of total) 47 46 43 21 Expected years of schooling (years) 12 14 13 14 120 Physicians density (per 1,000 people) 0.9 — 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,042 2005 2007 2009 2011 Jamaica Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 75 110 92a 109a Mobile cellular subscriptions (% prepaid) 96 97a 81a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 95 — 99 98 7 Mobile broadband subscriptions (per 100 people) 0.06 13.8a 14.3a 16.1a 6 Mobile broadband (% of total mobile subscriptions) 0.07 10.2a 15.4a 15.2a 5 Usage 4 Households with a mobile telephone (%) 69 92 84 84 3 Mobile voice usage (minutes per user per month) — — 25a 141a 2 Population using mobile Internet (%) — 8.5 22.9a 4.4 1 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Jamaica Mobile basket (% of GNI per capita) 4.1 3.0 2.9 3.7 Latin America & the Caribbean Region Japan High-income Japan group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 128 127 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 38,950 41,850 38,746 150 Rural population (% of total) 34 33 22 Expected years of schooling (years) 15 15 16 120 Physicians density (per 1,000 people) 2.1 2.1 2.8 90 Depositors with commercial banks (per 1,000 adults) 7,827 7,169 — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,601 2005 2007 2009 2011 Japan Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 76 95a 118a Mobile cellular subscriptions (% prepaid) 3 1a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 100 1.8 Mobile broadband subscriptions (per 100 people) 22.8 98.1a 69.6a 1.5 Mobile broadband (% of total mobile subscriptions) 31.0 95.3a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 90 93 93 0.6 Mobile voice usage (minutes per user per month) 149 134a 339 Population using mobile Internet (%) 54.2 61.8 24.3 0.3 Short Message Service (SMS) users (% of mobile users) — 81.0a 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability Japan Mobile basket (% of GNI per capita) 1.3 1.6 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 174 Information and Communications for Development 2012 World Bank • Mobile at a Glance Jordan Middle East & Upper-middle- North Africa Jordan income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 5 6 2,452 331 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,490 4,340 5,886 3,874 150 Rural population (% of total) 22 22 43 42 Expected years of schooling (years) 13 13 13 12 120 Physicians density (per 1,000 people) 2.4 2.5 1.7 1.4 90 Depositors with commercial banks (per 1,000 adults) — — — 443 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,402 2005 2007 2009 2011 Jordan Sector performance Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 58 121a 92a 89a Mobile cellular subscriptions (% prepaid) 87 91a 81a 87a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 99 99 — 10 Mobile broadband subscriptions (per 100 people) — 26.0a 14.3a — Mobile broadband (% of total mobile subscriptions) — 20.8a 15.4a — 8 Usage 6 Households with a mobile telephone (%) 51 98 84 — 4 Mobile voice usage (minutes per user per month) — — 325a — 2 Population using mobile Internet (%) — 13.2 22.9a 4.5 Short Message Service (SMS) users (% of mobile users) — 63.0a 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Jordan Mobile basket (% of GNI per capita) 7.6 2.9 2.9 3.6 Middle East & North Africa Region Kazakhstan Europe & Upper-middle- Central Asia Kazakhstan income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 15 16 2,452 405 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,930 7,580 5,886 7,272 150 Rural population (% of total) 43 42 43 36 Expected years of schooling (years) 15 15 13 13 120 Physicians density (per 1,000 people) 3.7 4.1 1.7 3.2 90 Depositors with commercial banks (per 1,000 adults) 831 874 — 894 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,236 2005 2007 2009 2011 Kazakhstan Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 36 137a 92a 125a Mobile cellular subscriptions (% prepaid) 80 91a 81a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 51 95 99 96 12 Mobile broadband subscriptions (per 100 people) — 3.4a 14.3a 22.6a 10 Mobile broadband (% of total mobile subscriptions) — 2.7a 15.4a 18.0a 8 Usage 6 Households with a mobile telephone (%) 27 81 84 82 4 Mobile voice usage (minutes per user per month) 59 157a 325a 288a Population using mobile Internet (%) — 4.8 22.9a 8.5 2 Short Message Service (SMS) users (% of mobile users) — 50.0 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Kazakhstan Mobile basket (% of GNI per capita) 8.4 2.3 2.9 3.1 Europe & Central Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 175 World Bank • Mobile at a Glance Kenya Low-income Sub-Saharan Kenya group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 36 41 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 520 810 530 1,188 150 Rural population (% of total) 79 78 72 63 120 Expected years of schooling (years) 10 11 9 9 Physicians density (per 1,000 people) 0.1 — 0.2 0.2 90 Depositors with commercial banks (per 1,000 adults) 115 370 — 167 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,229 2005 2007 2009 2011 Kenya Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 15 67a 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 98 99a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 62 89 — 72 60 Mobile broadband subscriptions (per 100 people) — 6.9a — 5.6a 50 Mobile broadband (% of total mobile subscriptions) — 10.3a — 10.1a 40 Usage 30 Households with a mobile telephone (%) 21 65 43 52 20 Mobile voice usage (minutes per user per month) — 82 — — 10 Population using mobile Internet (%) 0.03 11.3a — — 0 Short Message Service (SMS) users (% of mobile users) — 89.0a — — 2005 2006 2007 2008 2009 2010 Affordability Kenya Mobile basket (% of GNI per capita) 48.6 16.0 28.8 19.5 Sub-Saharan Africa Region Korea, Rep. High-income Korea, Rep. group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 48 49 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 16,900 19,890 38,746 150 Rural population (% of total) 19 18 22 Expected years of schooling (years) 16 17 16 120 Physicians density (per 1,000 people) 1.7 2.0 2.8 90 Depositors with commercial banks (per 1,000 adults) 3,997 4,522 — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,876 2005 2007 2009 2011 Korea, Rep. Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 80 109a 118a Mobile cellular subscriptions (% prepaid) 1.4 1.9a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 100 1.5 Mobile broadband subscriptions (per 100 people) 26.0 97.9a 69.6a Mobile broadband (% of total mobile subscriptions) 32.4 89.3a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 88 97 93 0.6 Mobile voice usage (minutes per user per month) 274 312 339 0.3 Population using mobile Internet (%) 27.0 40.8 24.3 Short Message Service (SMS) users (% of mobile users) — 99.8 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Korea, Rep. Mobile basket (% of GNI per capita) 1.2 0.9 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 176 Information and Communications for Development 2012 World Bank • Mobile at a Glance Kuwait High-income Kuwait group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 2 3 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 34,650 — 38,746 200 Rural population (% of total) 2 2 22 Expected years of schooling (years) 12 — 16 150 Physicians density (per 1,000 people) 1.8 1.8 2.8 Depositors with commercial banks (per 1,000 adults) — — — 100 Sector structure 50 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,746 2005 2007 2009 2011 Kuwait Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 101 183a 118a Mobile cellular subscriptions (% prepaid) 80 75a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 1.5 Mobile broadband subscriptions (per 100 people) 1.1 94.4a 69.6a Mobile broadband (% of total mobile subscriptions) 1.0 52.7a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) — — 93 0.6 Mobile voice usage (minutes per user per month) — — 339 0.3 Population using mobile Internet (%) — — 24.3 Short Message Service (SMS) users (% of mobile users) — 95.0 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Kuwait (—) Mobile basket (% of GNI per capita) — — 1.0 High-income group Kyrgyz Republic Europe & Low-income Central Asia Kyrgyz Republic group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 5 5 796 405 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 450 830 530 7,272 150 Rural population (% of total) 64 63 72 36 Expected years of schooling (years) 12 12 9 13 120 Physicians density (per 1,000 people) 2.4 — 0.2 3.2 90 Depositors with commercial banks (per 1,000 adults) — 181 — 894 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,253 2005 2007 2009 2011 Kyrgyz Republic Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 10 90 43a 125a Mobile cellular subscriptions (% prepaid) 91 94a 98a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) — 96 — 96 30 Mobile broadband subscriptions (per 100 people) — 3.5a — 22.6a 25 Mobile broadband (% of total mobile subscriptions) — 3.1a — 18.0a 20 Usage 15 Households with a mobile telephone (%) 10 88 43 82 Mobile voice usage (minutes per user per month) — — — 288a 10 Population using mobile Internet (%) — 2.6 — 8.5 5 Short Message Service (SMS) users (% of mobile users) — 48.0 — 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Kyrgyz Republic Mobile basket (% of GNI per capita) 24.1 5.2 28.8 3.1 Europe & Central Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 177 World Bank • Mobile at a Glance Lao People’s Democratic Republic Lao People’s Lower-middle- East Asia & Democratic Republic income group Pacific Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 6 6 2,519 1,962 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 470 1,040 1,623 3,696 150 Rural population (% of total) 73 67 61 54 120 Expected years of schooling (years) 9 9 10 12 Physicians density (per 1,000 people) 0.3 — 0.8 1.2 90 Depositors with commercial banks (per 1,000 adults) — 44 — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,670 2005 2007 2009 2011 Lao People's Democratic Republic Sector performance East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 11 53 78a 83a Mobile cellular subscriptions (% prepaid) 98 99a 96a 85a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 55 80 86 99 8 Mobile broadband subscriptions (per 100 people) — 3.3a 7.3a 11.6a Mobile broadband (% of total mobile subscriptions) — 6.8a 9.0a 14.4a 6 Usage 4 Households with a mobile telephone (%) — — 77 83 Mobile voice usage (minutes per user per month) — — 276a 367a 2 Population using mobile Internet (%) — — 2.9 22.4a Short Message Service (SMS) users (% of mobile users) — — 61.9a 84.0a 0 2005 2006 2007 2008 2009 2010 Affordability Lao People's Democratic Republic (—) Mobile basket (% of GNI per capita) — 7.3 7.2 5.7 East Asia & Pacific Region Latvia Europe & Upper-middle- Central Asia Latvia income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 2 2 2,452 405 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 6,810 11,640 5,886 7,272 150 Rural population (% of total) 32 32 43 36 Expected years of schooling (years) 16 15 13 13 120 Physicians density (per 1,000 people) 3.1 3.0 1.7 3.2 90 Depositors with commercial banks (per 1,000 adults) 932 1,286 — 894 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,891 2005 2007 2009 2011 Latvia Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 81 114a 92a 125a Mobile cellular subscriptions (% prepaid) 54 51a 81a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 98 — 99 96 12 Mobile broadband subscriptions (per 100 people) 0.1 35.3a 14.3a 22.6a 10 Mobile broadband (% of total mobile subscriptions) 0.2 30.7a 15.4a 18.0a 8 Usage 6 Households with a mobile telephone (%) 75 95 84 82 Mobile voice usage (minutes per user per month) — 248a 325a 288a 4 Population using mobile Internet (%) — 10.3 22.9a 8.5 2 Short Message Service (SMS) users (% of mobile users) — — 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Latvia Mobile basket (% of GNI per capita) 4.4 1.0 2.9 3.1 Europe & Central Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 178 Information and Communications for Development 2012 World Bank • Mobile at a Glance Lebanon Middle East & Upper-middle- North Africa Lebanon income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 4 4 2,452 331 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 5,710 8,880 5,886 3,874 150 Rural population (% of total) 13 13 43 42 Expected years of schooling (years) 13 14 13 12 120 Physicians density (per 1,000 people) 2.4 3.5 1.7 1.4 90 Depositors with commercial banks (per 1,000 adults) 742 873 — 443 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,015 2005 2007 2009 2011 Lebanon Sector performance Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 25 68 92a 89a Mobile cellular subscriptions (% prepaid) 83 84a 81a 87a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 95 99 — 10 Mobile broadband subscriptions (per 100 people) — 0.8a 14.3a — Mobile broadband (% of total mobile subscriptions) — 1.0a 15.4a — 8 Usage 6 Households with a mobile telephone (%) 50 80 84 — 4 Mobile voice usage (minutes per user per month) — — 325a — 2 Population using mobile Internet (%) — 9.4a 22.9a 4.5 Short Message Service (SMS) users (% of mobile users) — 87.0a 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Lebanon Mobile basket (% of GNI per capita) 6.9 3.7 2.9 3.6 Middle East & North Africa Region Lesotho Lower-middle- Sub-Saharan Lesotho income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 2 2 2,519 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 760 1,090 1,623 1,188 150 Rural population (% of total) 77 73 61 63 120 Expected years of schooling (years) 10 — 10 9 Physicians density (per 1,000 people) 0.1 — 0.8 0.2 90 Depositors with commercial banks (per 1,000 adults) 271 291 — 167 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 6,800 2005 2007 2009 2011 Lesotho Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 12 44 78a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 99a 96a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 29 — 86 72 60 Mobile broadband subscriptions (per 100 people) — 6.1a 7.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) — 11.1a 9.0a 10.1a 40 Usage 30 Households with a mobile telephone (%) — — 77 52 Mobile voice usage (minutes per user per month) — 29a 276a — 20 Population using mobile Internet (%) — — 2.9 — 10 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Lesotho (—) Mobile basket (% of GNI per capita) — 26.5 7.2 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 179 World Bank • Mobile at a Glance Libya Middle East & Upper-middle- North Africa Libya income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 6 6 2,452 331 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 6,460 12,320 5,886 3,874 200 Rural population (% of total) 23 22 43 42 Expected years of schooling (years) 17 — 13 12 150 Physicians density (per 1,000 people) 1.3 1.9 1.7 1.4 Depositors with commercial banks (per 1,000 adults) — — — 443 100 Sector structure 50 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 Libya Sector performance Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 35 172 92a 89a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 99a 81a 87a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 71 98 99 — 10 Mobile broadband subscriptions (per 100 people) — 49.8a 14.3a — Mobile broadband (% of total mobile subscriptions) — 39.9a 15.4a — 8 Usage 6 Households with a mobile telephone (%) — — 84 — 4 Mobile voice usage (minutes per user per month) — — 325a — 2 Population using mobile Internet (%) — — 22.9a 4.5 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Libya (—) Mobile basket (% of GNI per capita) — — 2.9 3.6 Middle East & North Africa Region Lithuania Europe & Upper-middle- Central Asia Lithuania income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 3 3 2,452 405 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 7,280 11,510 5,886 7,272 180 Rural population (% of total) 33 33 43 36 150 Expected years of schooling (years) 16 16 13 13 120 Physicians density (per 1,000 people) 4.0 3.6 1.7 3.2 Depositors with commercial banks (per 1,000 adults) — — — 894 90 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,396 2005 2007 2009 2011 Lithuania Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 128 151a 92a 125a Mobile cellular subscriptions (% prepaid) 68 56a 81a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 99 96 12 Mobile broadband subscriptions (per 100 people) 0.5 35.3a 14.3a 22.6a 10 Mobile broadband (% of total mobile subscriptions) 0.3 24.1a 15.4a 18.0a 8 Usage 6 Households with a mobile telephone (%) 73 92 84 82 Mobile voice usage (minutes per user per month) 77 174a 325a 288a 4 Population using mobile Internet (%) 3.2 15.3a 22.9a 8.5 2 Short Message Service (SMS) users (% of mobile users) — 79.0a 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Lithuania Mobile basket (% of GNI per capita) 2.2 1.0 2.9 3.1 Europe & Central Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 180 Information and Communications for Development 2012 World Bank • Mobile at a Glance Macedonia, Former Yugoslav Republic of Europe & Macedonia, Former Upper-middle- Central Asia Yugoslav Republic of income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 2 2 2,452 405 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,900 4,570 5,886 7,272 150 Rural population (% of total) 35 32 43 36 120 Expected years of schooling (years) 12 13 13 13 Physicians density (per 1,000 people) 2.5 2.6 1.7 3.2 90 Depositors with commercial banks (per 1,000 adults) — — — 894 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,315 2005 2007 2009 2011 Sector performance Macedonia, Former Yugoslav Republic of Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 55 110a 92a 125a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 86 62a 81a 82a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 99 96 12 Mobile broadband subscriptions (per 100 people) — 19.0a 14.3a 22.6a 10 Mobile broadband (% of total mobile subscriptions) — 16.8a 15.4a 18.0a 8 Usage 6 Households with a mobile telephone (%) 71 85 84 82 Mobile voice usage (minutes per user per month) — 142a 325a 288a 4 Population using mobile Internet (%) — 2.9 22.9a 8.5 2 Short Message Service (SMS) users (% of mobile users) — 52.0 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Macedonia, Former Yugoslav Republic of Mobile basket (% of GNI per capita) 10.4 6.1 2.9 3.1 Europe & Central Asia Region Madagascar Low-income Sub-Saharan Madagascar group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 18 21 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 300 430 530 1,188 80 Rural population (% of total) 72 70 72 63 Expected years of schooling (years) 9 11 9 9 60 Physicians density (per 1,000 people) 0.3 — 0.2 0.2 Depositors with commercial banks (per 1,000 adults) 18 45 — 167 40 Sector structure 20 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,528 0 2005 2007 2009 2011 Sector performance Madagascar Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 3 37 43a 57a Mobile cellular subscriptions (% prepaid) 98 99a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 23 — — 72 100 Mobile broadband subscriptions (per 100 people) — 1.6a — 5.6a Mobile broadband (% of total mobile subscriptions) — 5.4a — 10.1a 80 Usage 60 Households with a mobile telephone (%) 4 26 43 52 40 Mobile voice usage (minutes per user per month) — — — — Population using mobile Internet (%) — — — — 20 Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Madagascar Mobile basket (% of GNI per capita) 87.3 43.0 28.8 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 181 World Bank • Mobile at a Glance Malawi Low-income Sub-Saharan Malawi group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 13 15 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 220 330 530 1,188 80 Rural population (% of total) 83 80 72 63 Expected years of schooling (years) 9 — 9 9 60 Physicians density (per 1,000 people) 0.02 0.02 0.2 0.2 40 Depositors with commercial banks (per 1,000 adults) — — — 167 20 Sector structure Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,626 2005 2007 2009 2011 Malawi Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 3 26a 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 97 99a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 70 85 — 72 120 Mobile broadband subscriptions (per 100 people) — 0.6a — 5.6a 100 Mobile broadband (% of total mobile subscriptions) — 2.2a — 10.1a 80 Usage 60 Households with a mobile telephone (%) 3 39 43 52 40 Mobile voice usage (minutes per user per month) — — — — Population using mobile Internet (%) — — — — 20 Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Malawi Mobile basket (% of GNI per capita) 109.1 77.1 28.8 19.5 Sub-Saharan Africa Region Malaysia Upper-middle- East Asia & Malaysia income group Pacific Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 26 28 2,452 1,962 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 5,110 7,760 5,886 3,696 150 Rural population (% of total) 32 28 43 54 120 Expected years of schooling (years) 13 13 13 12 Physicians density (per 1,000 people) — 0.9 1.7 1.2 90 Depositors with commercial banks (per 1,000 adults) 1,892 1,458 — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,451 2005 2007 2009 2011 Malaysia Sector performance East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 75 124a 92a 83a Mobile cellular subscriptions (% prepaid) 85 77a 81a 85a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) — 95 99 99 8 Mobile broadband subscriptions (per 100 people) 0.3 38.2a 14.3a 11.6a Mobile broadband (% of total mobile subscriptions) 0.4 30.5a 15.4a 14.4a 6 Usage 4 Households with a mobile telephone (%) 55 90 84 83 Mobile voice usage (minutes per user per month) 162 223a 325a 367a 2 Population using mobile Internet (%) 3.8 18.0a 22.9a 22.4a Short Message Service (SMS) users (% of mobile users) — 76.0 74.4a 84.0a 0 2005 2006 2007 2008 2009 2010 Affordability Malaysia Mobile basket (% of GNI per capita) 2.0 1.2 2.9 5.7 East Asia & Pacific Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 182 Information and Communications for Development 2012 World Bank • Mobile at a Glance Mali Low-income Sub-Saharan Mali group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 13 15 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 390 600 530 1,188 150 Rural population (% of total) 70 67 72 63 120 Expected years of schooling (years) 7 8 9 9 Physicians density (per 1,000 people) 0.08 0.05 0.2 0.2 90 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,690 2005 2007 2009 2011 Mali Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 6 69a 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 98 100a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 20 — — 72 120 Mobile broadband subscriptions (per 100 people) — 3.3a — 5.6a 100 Mobile broadband (% of total mobile subscriptions) — 4.9a — 10.1a 80 Usage 60 Households with a mobile telephone (%) 15 21 43 52 40 Mobile voice usage (minutes per user per month) 30 — — — Population using mobile Internet (%) — — — — 20 Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Mali Mobile basket (% of GNI per capita) 104.3 28.8 28.8 19.5 Sub-Saharan Africa Region Mauritania Lower-middle- Sub-Saharan Mauritania income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 3 3 2,519 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 720 1,000 1,623 1,188 150 Rural population (% of total) 60 59 61 63 120 Expected years of schooling (years) 8 — 10 9 Physicians density (per 1,000 people) 0.1 0.1 0.8 0.2 90 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 Mauritania Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 24 84a 78a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 98 97a 96a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 26 62 86 72 60 Mobile broadband subscriptions (per 100 people) — — 7.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) — — 9.0a 10.1a 40 Usage 30 Households with a mobile telephone (%) — — 77 52 20 Mobile voice usage (minutes per user per month) — — 276a — Population using mobile Internet (%) — — 2.9 — 10 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Mauritania Mobile basket (% of GNI per capita) 19.1 17.5 7.2 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 183 World Bank • Mobile at a Glance Mauritius Upper-middle- Sub-Saharan Mauritius income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 1 1 2,452 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 5,360 7,850 5,886 1,188 150 Rural population (% of total) 58 57 43 63 120 Expected years of schooling (years) 13 14 13 9 Physicians density (per 1,000 people) 1.1 — 1.7 0.2 90 Depositors with commercial banks (per 1,000 adults) 322 465 — 167 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,366 2005 2007 2009 2011 Mauritius Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 53 93 92a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 93 93a 81a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 97 99 99 72 60 Mobile broadband subscriptions (per 100 people) 0.4 21.5a 14.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) 0.7 22.2a 15.4a 10.1a 40 Usage 30 Households with a mobile telephone (%) 60 88 84 52 20 Mobile voice usage (minutes per user per month) — — 325a — Population using mobile Internet (%) — — 22.9a — 10 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Mauritius Mobile basket (% of GNI per capita) 1.5 1.0 2.9 19.5 Sub-Saharan Africa Region Mexico Latin America & Upper-middle- the Caribbean Mexico income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 106 113 2,452 583 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 7,820 8,930 5,886 7,741 150 Rural population (% of total) 24 22 43 21 120 Expected years of schooling (years) 13 14 13 14 Physicians density (per 1,000 people) 2.9 2.0 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) — 1,205 — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,500 2005 2007 2009 2011 Sector performance Mexico Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 44 82a 92a 109a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 91 85a 81a 81a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 86 93 99 98 7 Mobile broadband subscriptions (per 100 people) 0.03 17.4a 14.3a 16.1a 6 Mobile broadband (% of total mobile subscriptions) 0.08 21.3a 15.4a 15.2a 5 Usage 4 Households with a mobile telephone (%) 42 71 84 84 3 Mobile voice usage (minutes per user per month) 97 203a 325a 141a 2 Population using mobile Internet (%) — 6.4a 22.9a 4.4 1 Short Message Service (SMS) users (% of mobile users) — 82.0a 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Mexico Mobile basket (% of GNI per capita) 2.5 2.3 2.9 3.7 Latin America & the Caribbean Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 184 Information and Communications for Development 2012 World Bank • Mobile at a Glance Moldova Lower-middle- Europe & Moldova income group Central Asia Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 4 4 2,519 405 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 890 1,810 1,623 7,272 150 Rural population (% of total) 57 59 61 36 120 Expected years of schooling (years) 12 12 10 13 Physicians density (per 1,000 people) 2.7 2.7 0.8 3.2 90 Depositors with commercial banks (per 1,000 adults) 811 1,197 — 894 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,077 2005 2007 2009 2011 Moldova Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 30 106a 78a 125a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 84 84a 96a 82a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 97 — 86 96 20 Mobile broadband subscriptions (per 100 people) — 26.6a 7.3a 22.6a Mobile broadband (% of total mobile subscriptions) — 27.2a 9.0a 18.0a 15 Usage 10 Households with a mobile telephone (%) 31 68 77 82 Mobile voice usage (minutes per user per month) — — 276a 288a 5 Population using mobile Internet (%) 0.3 3.4 2.9 8.5 Short Message Service (SMS) users (% of mobile users) — 33.0 61.9a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Moldova Mobile basket (% of GNI per capita) 17.4 8.4 7.2 3.1 Europe & Central Asia Region Mongolia Lower-middle- East Asia & Mongolia income group Pacific Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 3 3 2,519 1,962 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 890 1,870 1,623 3,696 150 Rural population (% of total) 43 43 61 54 120 Expected years of schooling (years) 13 14 10 12 Physicians density (per 1,000 people) — 2.8 0.8 1.2 90 Depositors with commercial banks (per 1,000 adults) 346 1,339 — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,102 2005 2007 2009 2011 Mongolia Sector performance East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 22 92 78a 83a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 91 96a 96a 85a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 29 85 86 99 8 Mobile broadband subscriptions (per 100 people) — 9.3a 7.3a 11.6a Mobile broadband (% of total mobile subscriptions) — 11.1a 9.0a 14.4a 6 Usage 4 Households with a mobile telephone (%) 28 86 77 83 Mobile voice usage (minutes per user per month) — — 276a 367a 2 Population using mobile Internet (%) — — 2.9 22.4a Short Message Service (SMS) users (% of mobile users) — — 61.9a 84.0a 0 2005 2006 2007 2008 2009 2010 Affordability Mongolia Mobile basket (% of GNI per capita) — 2.4 7.2 5.7 East Asia & Pacific Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 185 World Bank • Mobile at a Glance Morocco Middle East & Lower-middle- North Africa Morocco income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 30 32 2,519 331 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,960 2,850 1,623 3,874 150 Rural population (% of total) 45 43 61 42 120 Expected years of schooling (years) 10 — 10 12 Physicians density (per 1,000 people) 0.5 0.6 0.8 1.4 90 Depositors with commercial banks (per 1,000 adults) 301 694 — 443 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,108 2005 2007 2009 2011 Sector performance Morocco Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 41 113a 78a 89a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 96 96a 96a 87a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 98 98 86 — 25 Mobile broadband subscriptions (per 100 people) — 17.5a 7.3a — 20 Mobile broadband (% of total mobile subscriptions) — 15.4a 9.0a — Usage 15 Households with a mobile telephone (%) 59 84 77 — 10 Mobile voice usage (minutes per user per month) — 70 276a — 5 Population using mobile Internet (%) 0.04 3.4 2.9 4.5 Short Message Service (SMS) users (% of mobile users) 69.0 70.0 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Morocco Mobile basket (% of GNI per capita) 20.2 14.3 7.2 3.6 Middle East & North Africa Region Mozambique Low-income Sub-Saharan Mozambique group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 21 23 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 290 440 530 1,188 80 Rural population (% of total) 66 62 72 63 Expected years of schooling (years) 8 — 9 9 60 Physicians density (per 1,000 people) 0.03 0.03 0.2 0.2 40 Depositors with commercial banks (per 1,000 adults) — — — 167 20 Sector structure Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,050 2005 2007 2009 2011 Mozambique Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 7 25 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 98a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) — 32 — 72 70 Mobile broadband subscriptions (per 100 people) — 3.1a — 5.6a 60 Mobile broadband (% of total mobile subscriptions) — 8.7a — 10.1a 50 Usage 40 Households with a mobile telephone (%) — — 43 52 30 Mobile voice usage (minutes per user per month) — — — — 20 Population using mobile Internet (%) — — — — 10 Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Mozambique Mobile basket (% of GNI per capita) 66.3 46.4 28.8 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 186 Information and Communications for Development 2012 World Bank • Mobile at a Glance Myanmar Low-income East Asia & Myanmar group Pacific Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 46 48 796 1,962 Number per 100 people GNI per capita, World Bank Atlas method (current US$) — — 530 3,696 100 Rural population (% of total) 69 66 72 54 80 Expected years of schooling (years) 9 — 9 12 Physicians density (per 1,000 people) 0.4 0.5 0.2 1.2 60 Depositors with commercial banks (per 1,000 adults) — — — — 40 Sector structure 20 Number of mobile operators — 1 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 10,000 2005 2007 2009 2011 Myanmar Sector performance East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 0.3 1 43a 83a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 94 99a 98a 85a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 10 — — 99 8 Mobile broadband subscriptions (per 100 people) — 0.05a — 11.6a Mobile broadband (% of total mobile subscriptions) — 1.1a — 14.4a 6 Usage 4 Households with a mobile telephone (%) — — 43 83 Mobile voice usage (minutes per user per month) — — — 367a 2 Population using mobile Internet (%) — — — 22.4a Short Message Service (SMS) users (% of mobile users) — — — 84.0a 0 2005 2006 2007 2008 2009 2010 Affordability Myanmar (—) Mobile basket (% of GNI per capita) — — 28.8 5.7 East Asia & Pacific Region Namibia Upper-middle- Sub-Saharan Namibia income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 2 2 2,452 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 3,300 4,510 5,886 1,188 150 Rural population (% of total) 65 62 43 63 Expected years of schooling (years) 12 — 13 9 120 Physicians density (per 1,000 people) 0.3 — 1.7 0.2 90 Depositors with commercial banks (per 1,000 adults) — 624 — 167 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 6,717 2005 2007 2009 2011 Namibia Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 22 110a 92a 57a Mobile cellular subscriptions (% prepaid) 91 96a 81a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 88 — 99 72 60 Mobile broadband subscriptions (per 100 people) 0.1 11.1a 14.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) 0.4 10.0a 15.4a 10.1a 40 Usage 30 Households with a mobile telephone (%) 40 55 84 52 20 Mobile voice usage (minutes per user per month) — — 325a — Population using mobile Internet (%) — 7.0 22.9a — 10 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Namibia Mobile basket (% of GNI per capita) 9.6 4.5 2.9 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 187 World Bank • Mobile at a Glance Nepal Low-income South Asia Nepal group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 27 30 796 1,633 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 290 490 530 1,176 150 Rural population (% of total) 84 82 72 70 Expected years of schooling (years) — — 9 10 120 Physicians density (per 1,000 people) 0.2 — 0.2 0.6 90 Depositors with commercial banks (per 1,000 adults) — — — 249 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,826 2005 2007 2009 2011 Nepal Sector performance South Asia Region Access Mobile cellular subscriptions (per 100 people) 1 44a 43a 67a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 71 98a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 10 35 — 84 20 Mobile broadband subscriptions (per 100 people) — 0.4a — 3.3a Mobile broadband (% of total mobile subscriptions) — 0.8a — 4.6a 16 Usage 12 Households with a mobile telephone (%) 3 54 43 54 8 Mobile voice usage (minutes per user per month) — 123a — 305a 4 Population using mobile Internet (%) — — — 3.3a Short Message Service (SMS) users (% of mobile users) — — — 47.0a 0 2005 2006 2007 2008 2009 2010 Affordability Nepal Mobile basket (% of GNI per capita) 18.9 6.6 28.8 3.2 South Asia Region Netherlands High-income Netherlands group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 16 17 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 39,880 49,030 38,746 150 Rural population (% of total) 20 17 22 Expected years of schooling (years) 16 17 16 120 Physicians density (per 1,000 people) 3.7 2.9 2.8 90 Depositors with commercial banks (per 1,000 adults) 1,769 1,769 — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,789 2005 2007 2009 2011 Netherlands Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 97 128a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 57 41a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 — 100 1.8 Mobile broadband subscriptions (per 100 people) 1.6 50.7a 69.6a 1.5 Mobile broadband (% of total mobile subscriptions) 1.6 42.3a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 91 94 93 0.6 Mobile voice usage (minutes per user per month) 136 159a 339 Population using mobile Internet (%) — 15.6 24.3 0.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability Netherlands Mobile basket (% of GNI per capita) 1.5 0.8 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 188 Information and Communications for Development 2012 World Bank • Mobile at a Glance New Zealand High-income New Zealand group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 4 4 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 24,840 28,770 38,746 150 Rural population (% of total) 14 13 22 120 Expected years of schooling (years) 19 20 16 Physicians density (per 1,000 people) 2.4 2.7 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,229 2005 2007 2009 2011 New Zealand Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 85 108 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 70 65a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 98 97 100 2.5 Mobile broadband subscriptions (per 100 people) 4.2 77.1a 69.6a Mobile broadband (% of total mobile subscriptions) 4.5 64.1a 57.6a 2.0 Usage 1.5 Households with a mobile telephone (%) 86 90 93 1.0 Mobile voice usage (minutes per user per month) 83 — 339 0.5 Population using mobile Internet (%) — 18.3 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability New Zealand Mobile basket (% of GNI per capita) 1.9 1.7 1.0 High-income group Nicaragua Latin America & Lower-middle- the Caribbean Nicaragua income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 5 6 2,519 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 890 1,110 1,623 7,741 150 Rural population (% of total) 44 43 61 21 Expected years of schooling (years) 11 — 10 14 120 Physicians density (per 1,000 people) 0.4 — 0.8 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,512 2005 2007 2009 2011 Nicaragua Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 21 72a 78a 109a Mobile cellular subscriptions (% prepaid) 87 92a 96a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 70 — 86 98 40 Mobile broadband subscriptions (per 100 people) — 4.6a 7.3a 16.1a Mobile broadband (% of total mobile subscriptions) — 6.4a 9.0a 15.2a 30 Usage 20 Households with a mobile telephone (%) 24 62 77 84 Mobile voice usage (minutes per user per month) — — 276a 141a 10 Population using mobile Internet (%) — — 2.9 4.4 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Nicaragua Mobile basket (% of GNI per capita) 36.4 14.3 7.2 3.7 Latin America & the Caribbean Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 189 World Bank • Mobile at a Glance Niger Low-income Sub-Saharan Niger group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 13 16 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 260 370 530 1,188 150 Rural population (% of total) 84 83 72 63 Expected years of schooling (years) 4 5 9 9 120 Physicians density (per 1,000 people) 0.02 0.02 0.2 0.2 90 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,890 2005 2007 2009 2011 Niger Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 2 24 43a 57a Mobile cellular subscriptions (% prepaid) 99 99a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 15 — — 72 140 Mobile broadband subscriptions (per 100 people) — — — 5.6a 120 Mobile broadband (% of total mobile subscriptions) — — — 10.1a 100 Usage 80 Households with a mobile telephone (%) — 32 43 52 60 Mobile voice usage (minutes per user per month) — — — — 40 Population using mobile Internet (%) — — — — 20 Short Message Service (SMS) users (% of mobile users) — 11.0 — — 0 2005 2006 2007 2008 2009 2010 Affordability Niger Mobile basket (% of GNI per capita) 125.3 67.5 28.8 19.5 Sub-Saharan Africa Region Nigeria Lower-middle- Sub-Saharan Nigeria income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 140 158 2,519 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 630 1,230 1,623 1,188 80 Rural population (% of total) 54 50 61 63 Expected years of schooling (years) 9 — 10 9 60 Physicians density (per 1,000 people) 0.3 0.4 0.8 0.2 Depositors with commercial banks (per 1,000 adults) — — — 167 40 Sector structure 20 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,305 2005 2007 2009 2011 Nigeria Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 13 59a 78a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 97a 96a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 58 90 86 72 60 Mobile broadband subscriptions (per 100 people) 0.01 3.9a 7.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) 0.06 6.6a 9.0a 10.1a 40 Usage 30 Households with a mobile telephone (%) 40 60 77 52 20 Mobile voice usage (minutes per user per month) — — 276a — Population using mobile Internet (%) — 1.3 2.9 — 10 Short Message Service (SMS) users (% of mobile users) — 26.0 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Nigeria Mobile basket (% of GNI per capita) 49.1 13.4 7.2 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 190 Information and Communications for Development 2012 World Bank • Mobile at a Glance Norway High-income Norway group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 5 5 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 62,490 87,350 38,746 150 Rural population (% of total) 23 22 22 Expected years of schooling (years) 17 17 16 120 Physicians density (per 1,000 people) 3.8 4.2 2.8 90 Depositors with commercial banks (per 1,000 adults) 422 529 — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,478 2005 2007 2009 2011 Norway Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 103 115a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 37 32a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 1.4 Mobile broadband subscriptions (per 100 people) 1.9 62.2a 69.6a 1.2 Mobile broadband (% of total mobile subscriptions) 1.8 44.5a 57.6a 1.0 Usage 0.8 Households with a mobile telephone (%) 94 95 93 0.6 Mobile voice usage (minutes per user per month) 189 246a 339 0.4 Population using mobile Internet (%) 6.5 16.4 24.3 0.2 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Norway Mobile basket (% of GNI per capita) 0.5 0.3 1.0 High-income group Oman High-income Oman group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 2 3 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 11,190 18,260 38,746 200 Rural population (% of total) 29 28 22 Expected years of schooling (years) 11 12 16 150 Physicians density (per 1,000 people) 1.7 1.9 2.8 Depositors with commercial banks (per 1,000 adults) — 1,012 — 100 Sector structure 50 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,072 2005 2007 2009 2011 Oman Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 55 169a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 89 80a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 92 98 100 1.5 Mobile broadband subscriptions (per 100 people) — 26.5a 69.6a Mobile broadband (% of total mobile subscriptions) — 15.9a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 80 95 93 0.6 Mobile voice usage (minutes per user per month) — — 339 0.3 Population using mobile Internet (%) — — 24.3 Short Message Service (SMS) users (% of mobile users) — 82.0 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability Oman Mobile basket (% of GNI per capita) 0.9 0.6 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 191 World Bank • Mobile at a Glance Pakistan Lower-middle- South Asia Pakistan income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 159 174 2,519 1,633 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 710 1,050 1,623 1,176 150 Rural population (% of total) 65 63 61 70 120 Expected years of schooling (years) 6 7 10 10 Physicians density (per 1,000 people) 0.8 0.8 0.8 0.6 90 Depositors with commercial banks (per 1,000 adults) 131 249 — 249 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,282 2005 2007 2009 2011 Pakistan Sector performance South Asia Region Access Mobile cellular subscriptions (per 100 people) 8 64a 78a 67a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 97 98a 96a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 36 92 86 84 12 Mobile broadband subscriptions (per 100 people) — — 7.3a 3.3a 10 Mobile broadband (% of total mobile subscriptions) — — 9.0a 4.6a 8 Usage 6 Households with a mobile telephone (%) 33 48 77 54 4 Mobile voice usage (minutes per user per month) 151 205a 276a 305a Population using mobile Internet (%) — 1.7 2.9 3.3a 2 Short Message Service (SMS) users (% of mobile users) — 44.0a 61.9a 47.0a 0 2005 2006 2007 2008 2009 2010 Affordability Pakistan Mobile basket (% of GNI per capita) 8.5 2.9 7.2 3.2 South Asia Region Panama Latin America & Upper-middle- the Caribbean Panama income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 3 4 2,452 583 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 4,640 6,970 5,886 7,741 250 Rural population (% of total) 29 25 43 21 Expected years of schooling (years) 13 13 13 14 200 Physicians density (per 1,000 people) — — 1.7 1.8 150 Depositors with commercial banks (per 1,000 adults) — — — — 100 Sector structure 50 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 Panama Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 54 204a 92a 109a Mobile cellular subscriptions (% prepaid) 92 94a 81a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 75 91 99 98 12 Mobile broadband subscriptions (per 100 people) — 5.5a 14.3a 16.1a 10 Mobile broadband (% of total mobile subscriptions) — 3.8a 15.4a 15.2a 8 Usage 6 Households with a mobile telephone (%) 64 84 84 84 4 Mobile voice usage (minutes per user per month) — — 325a 141a Population using mobile Internet (%) — — 22.9a 4.4 2 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Panama Mobile basket (% of GNI per capita) 9.6 1.5 2.9 3.7 Latin America & the Caribbean Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 192 Information and Communications for Development 2012 World Bank • Mobile at a Glance Papua New Guinea Lower-middle- East Asia & Papua New Guinea income group Pacific Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 6 7 2,519 1,962 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 680 1,300 1,623 3,696 150 Rural population (% of total) 87 88 61 54 Expected years of schooling (years) — — 10 12 120 Physicians density (per 1,000 people) — 0.1 0.8 1.2 90 Depositors with commercial banks (per 1,000 adults) 157 178 — — 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 Papua New Guinea Sector performance East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 1 28 78a 83a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 98 99a 96a 85a Percentage of GNI per capita Population covered by a mobile-cellular network (%) — — 86 99 25 Mobile broadband subscriptions (per 100 people) — — 7.3a 11.6a Mobile broadband (% of total mobile subscriptions) — — 9.0a 14.4a 20 Usage 15 Households with a mobile telephone (%) — — 77 83 10 Mobile voice usage (minutes per user per month) — — 276a 367a 5 Population using mobile Internet (%) — — 2.9 22.4a Short Message Service (SMS) users (% of mobile users) — — 61.9a 84.0a 0 2005 2006 2007 2008 2009 2010 Affordability Papua New Guinea (—) Mobile basket (% of GNI per capita) — 21.5 7.2 5.7 East Asia & Pacific Region Paraguay Latin America & Lower-middle- the Caribbean Paraguay income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 6 6 2,519 583 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,220 2,720 1,623 7,741 150 Rural population (% of total) 42 39 61 21 Expected years of schooling (years) 12 12 10 14 120 Physicians density (per 1,000 people) — — 0.8 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,655 2005 2007 2009 2011 Paraguay Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 32 96 78a 109a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 87 84a 96a 81a Percentage of GNI per capita Population covered by a mobile-cellular network (%) — 94 86 98 10 Mobile broadband subscriptions (per 100 people) — 4.5a 7.3a 16.1a Mobile broadband (% of total mobile subscriptions) — 4.4a 9.0a 15.2a 8 Usage 6 Households with a mobile telephone (%) 49 85 77 84 4 Mobile voice usage (minutes per user per month) — — 276a 141a 2 Population using mobile Internet (%) — — 2.9 4.4 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Paraguay Mobile basket (% of GNI per capita) 7.7 3.8 7.2 3.7 Latin America & the Caribbean Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 193 World Bank • Mobile at a Glance Peru Latin America & Upper-middle- the Caribbean Peru income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 28 29 2,452 583 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,680 4,700 5,886 7,741 150 Rural population (% of total) 29 28 43 21 Expected years of schooling (years) 13 — 13 14 120 Physicians density (per 1,000 people) — 0.9 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) 237 436 — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,115 2005 2007 2009 2011 Peru Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 20 101a 92a 109a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 82 79a 81a 81a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 87 97 99 98 16 Mobile broadband subscriptions (per 100 people) — 9.1a 14.3a 16.1a Mobile broadband (% of total mobile subscriptions) — 10.0a 15.4a 15.2a 12 Usage 8 Households with a mobile telephone (%) 21 73 84 84 Mobile voice usage (minutes per user per month) 74 109a 325a 141a 4 Population using mobile Internet (%) — 5.8 22.9a 4.4 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Peru Mobile basket (% of GNI per capita) 14.9 11.0 2.9 3.7 Latin America & the Caribbean Region Philippines Lower-middle- East Asia & Philippines income group Pacific Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 86 93 2,519 1,962 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,210 2,060 1,623 3,696 150 Rural population (% of total) 37 34 61 54 Expected years of schooling (years) 12 12 10 12 120 Physicians density (per 1,000 people) 1.2 — 0.8 1.2 90 Depositors with commercial banks (per 1,000 adults) 370 488 — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,931 2005 2007 2009 2011 Philippines Sector performance East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 41 101a 78a 83a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 97 96a 96a 85a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 99 86 99 8 Mobile broadband subscriptions (per 100 people) 0.0 23.1a 7.3a 11.6a Mobile broadband (% of total mobile subscriptions) 0.0 23.2a 9.0a 14.4a 6 Usage 4 Households with a mobile telephone (%) 47 80 77 83 Mobile voice usage (minutes per user per month) — 69a 276a 367a 2 Population using mobile Internet (%) 0.5 9.8a 2.9 22.4a Short Message Service (SMS) users (% of mobile users) — 97.0 61.9a 84.0a 0 2005 2006 2007 2008 2009 2010 Affordability Philippines Mobile basket (% of GNI per capita) 6.9 5.9 7.2 5.7 East Asia & Pacific Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 194 Information and Communications for Development 2012 World Bank • Mobile at a Glance Poland High-income Poland group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 38 38 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 7,290 12,440 38,746 150 Rural population (% of total) 39 39 22 120 Expected years of schooling (years) 15 15 16 Physicians density (per 1,000 people) 2.0 2.2 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,692 2005 2007 2009 2011 Poland Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 76 111a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 62 51a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 99 100 2.5 Mobile broadband subscriptions (per 100 people) 0.05 43.4a 69.6a Mobile broadband (% of total mobile subscriptions) 0.06 33.2a 57.6a 2.0 Usage 1.5 Households with a mobile telephone (%) 62 88 93 1.0 Mobile voice usage (minutes per user per month) 67 148a 339 0.5 Population using mobile Internet (%) — 3.7 24.3 Short Message Service (SMS) users (% of mobile users) — 85.0a 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Poland Mobile basket (% of GNI per capita) 2.3 1.5 1.0 High-income group Portugal High-income Portugal group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 11 11 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 18,060 21,870 38,746 180 Rural population (% of total) 42 39 22 150 Expected years of schooling (years) 15 16 16 120 Physicians density (per 1,000 people) 3.4 3.9 2.8 Depositors with commercial banks (per 1,000 adults) 2,440 2,806 — 90 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,718 2005 2007 2009 2011 Portugal Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 109 158a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 81 73a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 99 100 1.8 Mobile broadband subscriptions (per 100 people) 8.7 90.2a 69.6a 1.5 Mobile broadband (% of total mobile subscriptions) 7.7 54.1a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 83 88 93 0.6 Mobile voice usage (minutes per user per month) 118 121a 339 Population using mobile Internet (%) 2.4 8.3a 24.3 0.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Portugal Mobile basket (% of GNI per capita) 1.3 1.3 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 195 World Bank • Mobile at a Glance Puerto Rico High-income Puerto Rico group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 4 4 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 14,190 15,500 38,746 150 Rural population (% of total) 2 1 22 Expected years of schooling (years) — — 16 120 Physicians density (per 1,000 people) — — 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — — 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 Puerto Rico Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 51 74 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 10 17a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) — — 100 1.5 Mobile broadband subscriptions (per 100 people) 0.4 11.7a 69.6a Mobile broadband (% of total mobile subscriptions) 0.8 15.8a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) — — 93 0.6 Mobile voice usage (minutes per user per month) — — 339 0.3 Population using mobile Internet (%) — — 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability Puerto Rico (—) Mobile basket (% of GNI per capita) — — 1.0 High-income group Qatar High-income Qatar group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 0.82 2 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) — — 38,746 180 Rural population (% of total) 5 4 22 150 Expected years of schooling (years) 14 12 16 120 Physicians density (per 1,000 people) 2.6 — 2.8 90 Depositors with commercial banks (per 1,000 adults) 672 770 — 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 6,250 2005 2007 2009 2011 Qatar Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 87 153a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 81 87a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 100 1.8 Mobile broadband subscriptions (per 100 people) 0.7 43.5a 69.6a 1.5 Mobile broadband (% of total mobile subscriptions) 0.7 28.4a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 97 99 93 0.6 Mobile voice usage (minutes per user per month) — — 339 Population using mobile Internet (%) — 32.4 24.3 0.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Qatar (—) Mobile basket (% of GNI per capita) — — 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 196 Information and Communications for Development 2012 World Bank • Mobile at a Glance Romania Europe & Upper-middle- Central Asia Romania income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 22 21 2,452 405 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 3,920 7,850 5,886 7,272 150 Rural population (% of total) 46 45 43 36 Expected years of schooling (years) 14 15 13 13 120 Physicians density (per 1,000 people) 1.9 2.3 1.7 3.2 90 Depositors with commercial banks (per 1,000 adults) — — — 894 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,130 2005 2007 2009 2011 Romania Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 62 110a 92a 125a Mobile cellular subscriptions (% prepaid) 67 68a 81a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 97 100 99 96 12 Mobile broadband subscriptions (per 100 people) 0.7 38.8a 14.3a 22.6a 10 Mobile broadband (% of total mobile subscriptions) 1.1 30.0a 15.4a 18.0a 8 Usage 6 Households with a mobile telephone (%) 50 77 84 82 Mobile voice usage (minutes per user per month) — 213a 325a 288a 4 Population using mobile Internet (%) 0.4 8.0a 22.9a 8.5 2 Short Message Service (SMS) users (% of mobile users) — — 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Romania Mobile basket (% of GNI per capita) 4.5 3.1 2.9 3.1 Europe & Central Asia Region Russian Federation Europe & Russian Upper-middle- Central Asia Federation income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 143 142 2,452 405 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 4,460 9,900 5,886 7,272 180 Rural population (% of total) 27 27 43 36 150 Expected years of schooling (years) 14 14 13 13 Physicians density (per 1,000 people) 4.0 — 1.7 3.2 120 Depositors with commercial banks (per 1,000 adults) — — — 894 90 60 Sector structure 30 Number of mobile operators — 6 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,570 2005 2007 2009 2011 Russian Federation Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 84 160a 92a 125a Mobile cellular subscriptions (% prepaid) 91 88a 81a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 95 — 99 96 12 Mobile broadband subscriptions (per 100 people) 0.03 25.0a 14.3a 22.6a Mobile broadband (% of total mobile subscriptions) 0.03 15.5a 15.4a 18.0a 10 8 Usage 6 Households with a mobile telephone (%) 32 90 84 82 Mobile voice usage (minutes per user per month) 136 275a 325a 288a 4 Population using mobile Internet (%) 0.3 17.0a 22.9a 8.5 2 Short Message Service (SMS) users (% of mobile users) — 75.0a 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Russian Federation Mobile basket (% of GNI per capita) 2.9 1.1 2.9 3.1 Europe & Central Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 197 World Bank • Mobile at a Glance Rwanda Low-income Sub-Saharan Rwanda group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 9 11 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 270 520 530 1,188 80 Rural population (% of total) 83 81 72 63 Expected years of schooling (years) 9 11 9 9 60 Physicians density (per 1,000 people) 0.02 — 0.2 0.2 40 Depositors with commercial banks (per 1,000 adults) 9 218 — 167 20 Sector structure Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,609 2005 2007 2009 2011 Rwanda Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 2 39a 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 100a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 75 96 — 72 120 Mobile broadband subscriptions (per 100 people) — 6.2a — 5.6a 100 Mobile broadband (% of total mobile subscriptions) — 16.7a — 10.1a 80 Usage 60 Households with a mobile telephone (%) 5 40 43 52 Mobile voice usage (minutes per user per month) — 96a — — 40 Population using mobile Internet (%) — 0.5 — — 20 Short Message Service (SMS) users (% of mobile users) — 35.0 — — 0 2005 2006 2007 2008 2009 2010 Affordability Rwanda Mobile basket (% of GNI per capita) 97.0 32.1 28.8 19.5 Sub-Saharan Africa Region Saudi Arabia High-income Saudi Arabia group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 24 27 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 12,230 16,190 38,746 250 Rural population (% of total) 19 16 22 200 Expected years of schooling (years) 13 14 16 Physicians density (per 1,000 people) 1.4 0.9 2.8 150 Depositors with commercial banks (per 1,000 adults) 480 780 — 100 Sector structure 50 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,802 2005 2007 2009 2011 Saudi Arabia Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 59 200a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 85 81a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 96 99 100 1.8 Mobile broadband subscriptions (per 100 people) 0.6 86.2a 69.6a 1.5 Mobile broadband (% of total mobile subscriptions) 0.7 42.8a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 95 99 93 0.6 Mobile voice usage (minutes per user per month) — — 339 Population using mobile Internet (%) — 7.3 24.3 0.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability Saudi Arabia Mobile basket (% of GNI per capita) 1.7 1.0 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 198 Information and Communications for Development 2012 World Bank • Mobile at a Glance Senegal Lower-middle- Sub-Saharan Senegal income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 11 12 2,519 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 800 1,080 1,623 1,188 150 Rural population (% of total) 58 57 61 63 120 Expected years of schooling (years) 7 7 10 9 Physicians density (per 1,000 people) 0.1 0.1 0.8 0.2 90 Depositors with commercial banks (per 1,000 adults) — — — 167 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,893 2005 2007 2009 2011 Senegal Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 16 74a 78a 57a Mobile cellular subscriptions (% prepaid) 98 99a 96a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 85 90 86 72 60 Mobile broadband subscriptions (per 100 people) — 6.9a 7.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) — 8.8a 9.0a 10.1a 40 Usage Households with a mobile telephone (%) 30 86 77 52 30 Mobile voice usage (minutes per user per month) — — 276a — 20 Population using mobile Internet (%) — 0.3 2.9 — 10 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Senegal Mobile basket (% of GNI per capita) 38.7 14.1 7.2 19.5 Sub-Saharan Africa Region Serbia Europe & Upper-middle- Central Asia Serbia income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 7 7 2,452 405 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 3,430 5,630 5,886 7,272 180 Rural population (% of total) 49 48 43 36 150 Expected years of schooling (years) 14 14 13 13 Physicians density (per 1,000 people) 2.0 2.1 1.7 3.2 120 Depositors with commercial banks (per 1,000 adults) — — — 894 90 60 Sector structure 30 Number of mobile operators — — 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 Serbia Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 74 143a 92a 125a Mobile cellular subscriptions (% prepaid) 87 70a 81a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 96 97 99 96 12 Mobile broadband subscriptions (per 100 people) 0.3 19.5a 14.3a 22.6a 10 Mobile broadband (% of total mobile subscriptions) 0.3 13.6a 15.4a 18.0a 8 Usage 6 Households with a mobile telephone (%) 70 82 84 82 4 Mobile voice usage (minutes per user per month) — — 325a 288a Population using mobile Internet (%) — 4.1 22.9a 8.5 2 Short Message Service (SMS) users (% of mobile users) — 64.0 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Serbia Mobile basket (% of GNI per capita) 4.0 2.5 2.9 3.1 Europe & Central Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 199 World Bank • Mobile at a Glance Sierra Leone Low-income Sub-Saharan Sierra Leone group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 5 6 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 230 340 530 1,188 80 Rural population (% of total) 63 62 72 63 Expected years of schooling (years) — — 9 9 60 Physicians density (per 1,000 people) 0.03 0.02 0.2 0.2 Depositors with commercial banks (per 1,000 adults) 61 190 — 167 40 Sector structure 20 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,522 2005 2007 2009 2011 Sierra Leone Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 14 34 43a 57a Mobile cellular subscriptions (% prepaid) 99 99a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 70 — — 72 120 Mobile broadband subscriptions (per 100 people) — 0.8a — 5.6a Mobile broadband (% of total mobile subscriptions) — 1.7a — 10.1a 90 Usage 60 Households with a mobile telephone (%) — 37 43 52 Mobile voice usage (minutes per user per month) — — — — 30 Population using mobile Internet (%) — — — — Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Sierra Leone Mobile basket (% of GNI per capita) 82.6 — 28.8 19.5 Sub-Saharan Africa Region Singapore High-income Singapore group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 4 5 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 27,180 40,070 38,746 180 Rural population (% of total) 0 0 22 150 Expected years of schooling (years) — — 16 120 Physicians density (per 1,000 people) 1.5 1.8 2.8 90 Depositors with commercial banks (per 1,000 adults) 2,031 2,134 — 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,520 0 2005 2007 2009 2011 Sector performance Singapore High-income group Access Mobile cellular subscriptions (per 100 people) 103 150a 118a Mobile cellular subscriptions (% prepaid) 35 48a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 1.5 Mobile broadband subscriptions (per 100 people) 4.1 81.9a 69.6a Mobile broadband (% of total mobile subscriptions) 4.0 54.4a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 91 96 93 0.6 Mobile voice usage (minutes per user per month) 312 366a 339 0.3 Population using mobile Internet (%) — 25.6 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Singapore Mobile basket (% of GNI per capita) 0.4 0.2 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 200 Information and Communications for Development 2012 World Bank • Mobile at a Glance Slovak Republic High-income Slovak Republic group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 5 5 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 11,040 16,840 38,746 150 Rural population (% of total) 44 43 22 Expected years of schooling (years) 14 15 16 120 Physicians density (per 1,000 people) 3.1 — 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,918 2005 2007 2009 2011 Slovak Republic Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 84 110a 118a Mobile cellular subscriptions (% prepaid) 58 49a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 5 Mobile broadband subscriptions (per 100 people) 2.2 40.9a 69.6a Mobile broadband (% of total mobile subscriptions) 2.4 34.6a 57.6a 4 Usage 3 Households with a mobile telephone (%) 85 88 93 2 Mobile voice usage (minutes per user per month) — — 339 1 Population using mobile Internet (%) — 17.9 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Slovak Republic Mobile basket (% of GNI per capita) 1.4 2.7 1.0 High-income group Slovenia High-income Slovenia group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 2 2 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 18,070 23,900 38,746 150 Rural population (% of total) 51 52 22 Expected years of schooling (years) 16 17 16 120 Physicians density (per 1,000 people) 2.4 2.5 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,100 2005 2007 2009 2011 Slovenia Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 88 105a 118a Mobile cellular subscriptions (% prepaid) 47 33a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 100 1.5 Mobile broadband subscriptions (per 100 people) 1.3 43.7a 69.6a Mobile broadband (% of total mobile subscriptions) 1.5 44.0a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 87 94 93 0.6 Mobile voice usage (minutes per user per month) 134 151 339 0.3 Population using mobile Internet (%) 2.5 13.9 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Slovenia Mobile basket (% of GNI per capita) 1.3 1.0 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 201 World Bank • Mobile at a Glance South Africa Upper-middle- Sub-Saharan South Africa income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 47 50 2,452 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 4,850 6,090 5,886 1,188 150 Rural population (% of total) 41 38 43 63 120 Expected years of schooling (years) — — 13 9 Physicians density (per 1,000 people) 0.8 — 1.7 0.2 90 Depositors with commercial banks (per 1,000 adults) 522 978 — 167 60 Sector structure 30 Number of mobile operators — 4 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,850 0 2005 2007 2009 2011 South Africa Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 72 128a 92a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 85 82a 81a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 96 — 99 72 60 Mobile broadband subscriptions (per 100 people) 0.4 27.8a 14.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) 0.6 21.9a 15.4a 10.1a 40 Usage 30 Households with a mobile telephone (%) 62 86 84 52 Mobile voice usage (minutes per user per month) 98 110 325a — 20 Population using mobile Internet (%) 0.2 6.2 22.9a — 10 Short Message Service (SMS) users (% of mobile users) — 50.0 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability South Africa Mobile basket (% of GNI per capita) 6.1 4.6 2.9 19.5 Sub-Saharan Africa Region Spain High-income Spain group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 43 46 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 25,450 31,750 38,746 150 Rural population (% of total) 23 23 22 120 Expected years of schooling (years) 16 17 16 Physicians density (per 1,000 people) 3.8 4.0 2.8 90 Depositors with commercial banks (per 1,000 adults) 707 775 — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,340 2005 2007 2009 2011 Spain Sector performance High-income group Access a a Mobile cellular subscriptions (per 100 people) 98 121 118 Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 48 35a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 100 2.5 Mobile broadband subscriptions (per 100 people) 2.1 64.2a 69.6a 2.0 Mobile broadband (% of total mobile subscriptions) 2.1 50.5a 57.6a Usage 1.5 Households with a mobile telephone (%) 80 95 93 1.0 Mobile voice usage (minutes per user per month) 144 152a 339 0.5 Population using mobile Internet (%) 3.9 13.8 24.3 Short Message Service (SMS) users (% of mobile users) — 80.8 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Spain Mobile basket (% of GNI per capita) 1.7 2.0 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 202 Information and Communications for Development 2012 World Bank • Mobile at a Glance Sri Lanka Lower-middle- South Asia Sri Lanka income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 20 21 2,519 1,633 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,190 2,240 1,623 1,176 150 Rural population (% of total) 85 85 61 70 Expected years of schooling (years) 13 — 10 10 120 Physicians density (per 1,000 people) 0.5 — 0.8 0.6 90 Depositors with commercial banks (per 1,000 adults) — — — 249 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,810 2005 2007 2009 2011 Sri Lanka Sector performance South Asia Region Access Mobile cellular subscriptions (per 100 people) 17 87a 78a 67a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 85 94a 96a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 85 98 86 84 12 Mobile broadband subscriptions (per 100 people) 0.03 9.8a 7.3a 3.3a 10 Mobile broadband (% of total mobile subscriptions) 0.10 10.5a 9.0a 4.6a 8 Usage 6 Households with a mobile telephone (%) 20 60 77 54 Mobile voice usage (minutes per user per month) — 121 276a 305a 4 Population using mobile Internet (%) — 4.4 2.9 3.3a 2 Short Message Service (SMS) users (% of mobile users) — — 61.9a 47.0a 0 2005 2006 2007 2008 2009 2010 Affordability Sri Lanka Mobile basket (% of GNI per capita) 6.5 1.0 7.2 3.2 South Asia Region Sudan Lower-middle- Sub-Saharan Sudanb income group Africa Region 2005 2010 2010 2010 Economic and social context Population (total, million) 38 44 2,519 853 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 610 1,270 1,623 1,188 80 Rural population (% of total) 59 55 61 63 Expected years of schooling (years) — — 10 9 60 Physicians density (per 1,000 people) 0.3 0.3 0.8 0.2 Depositors with commercial banks (per 1,000 adults) — — — 167 40 Sector structure 20 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,402 0 2005 2007 2009 2011 Sudan Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 5 50a 78a 57a Mobile cellular subscriptions (% prepaid) 97 99a 96a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 34 66 86 72 60 Mobile broadband subscriptions (per 100 people) 0.03 8.6a 7.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) 0.23 15.7a 9.0a 10.1a 40 Usage 30 Households with a mobile telephone (%) — — 77 52 Mobile voice usage (minutes per user per month) — — 276a — 20 Population using mobile Internet (%) — — 2.9 — 10 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Sudan Mobile basket (% of GNI per capita) 17.7 3.3 7.2 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. b. Data for Sudan include South Sudan. Information and Communications for Development 2012 203 World Bank • Mobile at a Glance Swaziland Lower-middle- Sub-Saharan Swaziland income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 1 1 2,519 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,600 2,930 1,623 1,188 150 Rural population (% of total) 76 75 61 63 120 Expected years of schooling (years) 10 — 10 9 Physicians density (per 1,000 people) 0.2 — 0.8 0.2 90 Depositors with commercial banks (per 1,000 adults) 352 455 — 167 60 Sector structure 30 Number of mobile operators — 1 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 10,000 2005 2007 2009 2011 Swaziland Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 20 78a 78a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 98 98a 96a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 90 91 86 72 60 Mobile broadband subscriptions (per 100 people) — 0.4a 7.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) — 0.5a 9.0a 10.1a 40 Usage 30 Households with a mobile telephone (%) 60 — 77 52 20 Mobile voice usage (minutes per user per month) 305 79 276a — Population using mobile Internet (%) — — 2.9 — 10 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Swaziland Mobile basket (% of GNI per capita) 14.2 9.9 7.2 19.5 Sub-Saharan Africa Region Sweden High-income Sweden group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 9 9 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 42,920 50,100 38,746 150 Rural population (% of total) 16 15 22 Expected years of schooling (years) 16 16 16 120 Physicians density (per 1,000 people) 3.6 3.8 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,990 2005 2007 2009 2011 Sweden Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 101 139a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 56 38a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 99 100 1.5 Mobile broadband subscriptions (per 100 people) 7.2 114.2a 69.6a Mobile broadband (% of total mobile subscriptions) 6.5 77.1a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 95 97 93 0.6 Mobile voice usage (minutes per user per month) 140 242a 339 0.3 Population using mobile Internet (%) 5.4 19.9 24.3 Short Message Service (SMS) users (% of mobile users) — 91.0a 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Sweden Mobile basket (% of GNI per capita) 0.9 0.4 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 204 Information and Communications for Development 2012 World Bank • Mobile at a Glance Switzerland High-income Switzerland group 2005 2010 2010 Economic and social context Population (total, million) 7 8 1,127 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 56,870 71,520 38,746 150 Rural population (% of total) 27 26 22 120 Expected years of schooling (years) 15 16 16 Physicians density (per 1,000 people) 4.0 4.1 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,371 2005 2007 2009 2011 Switzerland Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 92 123 118a Mobile cellular subscriptions (% prepaid) 39 39a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 1.5 Mobile broadband subscriptions (per 100 people) 1.4 57.1a 69.6a 1.2 Mobile broadband (% of total mobile subscriptions) 1.5 45.6a 57.6a Usage 0.9 Households with a mobile telephone (%) 84 92 93 0.6 Mobile voice usage (minutes per user per month) 124 130a 339 0.3 Population using mobile Internet (%) — 19.2 24.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability Switzerland Mobile basket (% of GNI per capita) 1.2 1.0 1.0 High-income group Syrian Arab Republic Middle East & Lower-middle- North Africa Syrian Arab Republic income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 18 20 2,519 331 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,500 2,750 1,623 3,874 150 Rural population (% of total) 47 45 61 42 Expected years of schooling (years) 11 — 10 12 120 Physicians density (per 1,000 people) 0.5 1.5 0.8 1.4 90 Depositors with commercial banks (per 1,000 adults) — 220 — 443 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,050 2005 2007 2009 2011 Syrian Arab Republic Sector performance Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 16 60a 78a 89a Mobile cellular subscriptions (% prepaid) 62 84a 96a 87a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 92 98 86 — 10 Mobile broadband subscriptions (per 100 people) — 2.2a 7.3a — Mobile broadband (% of total mobile subscriptions) — 3.7a 9.0a — 8 Usage 6 Households with a mobile telephone (%) — — 77 — 4 Mobile voice usage (minutes per user per month) — — 276a — 2 Population using mobile Internet (%) — — 2.9 4.5 Short Message Service (SMS) users (% of mobile users) — 93.0 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Syrian Arab Republic (—) Mobile basket (% of GNI per capita) — 8.7 7.2 3.6 Middle East & North Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 205 World Bank • Mobile at a Glance Tajikistan Europe & Low-income Central Asia Tajikistan group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 6 7 796 405 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 340 800 530 7,272 150 Rural population (% of total) 74 74 72 36 120 Expected years of schooling (years) 11 11 9 13 Physicians density (per 1,000 people) 2.0 2.1 0.2 3.2 90 Depositors with commercial banks (per 1,000 adults) — — — 894 60 Sector structure 30 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,545 2005 2007 2009 2011 Tajikistan Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 4 85a 43a 125a Mobile cellular subscriptions (% prepaid) 87 95a 98a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) — — — 96 100 Mobile broadband subscriptions (per 100 people) 0.01 11.2a — 22.6a 80 Mobile broadband (% of total mobile subscriptions) 0.16 11.9a — 18.0a Usage 60 Households with a mobile telephone (%) 11 80 43 82 40 Mobile voice usage (minutes per user per month) 216 182 — 288a 20 Population using mobile Internet (%) — 2.0 — 8.5 Short Message Service (SMS) users (% of mobile users) — 22.0 — 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Tajikistan Mobile basket (% of GNI per capita) 90.3 2.7 28.8 3.1 Europe & Central Asia Region Tanzania Low-income Sub-Saharan Tanzania group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 39 45 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 390 540 530 1,188 80 Rural population (% of total) 76 74 72 63 Expected years of schooling (years) 8 — 9 9 60 Physicians density (per 1,000 people) 0.01 — 0.2 0.2 Depositors with commercial banks (per 1,000 adults) 83 131 — 167 40 Sector structure 20 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,082 2005 2007 2009 2011 Tanzania Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 8 56a 43a 57a Mobile cellular subscriptions (% prepaid) 100 100a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 45 85 — 72 60 Mobile broadband subscriptions (per 100 people) 0.1 3.8a — 5.6a 50 Mobile broadband (% of total mobile subscriptions) 0.4 6.9a — 10.1a 40 Usage 30 Households with a mobile telephone (%) 9 45 43 52 20 Mobile voice usage (minutes per user per month) — 68a — — Population using mobile Internet (%) — — — — 10 Short Message Service (SMS) users (% of mobile users) — 51.0 — — 0 2005 2006 2007 2008 2009 2010 Affordability Tanzania Mobile basket (% of GNI per capita) 52.4 21.6 28.8 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 206 Information and Communications for Development 2012 World Bank • Mobile at a Glance Thailand Upper-middle- East Asia & Thailand income group Pacific Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 67 69 2,452 1,962 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 2,560 4,150 5,886 3,696 150 Rural population (% of total) 68 66 43 54 120 Expected years of schooling (years) 12 12 13 12 Physicians density (per 1,000 people) 0.3 0.3 1.7 1.2 90 Depositors with commercial banks (per 1,000 adults) 984 1,120 — — 60 Sector structure 30 Number of mobile operators — 5 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,409 0 2005 2007 2009 2011 Thailand Sector performance East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 47 109a 92a 83a Mobile cellular subscriptions (% prepaid) 85 90a 81a 85a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) — — 99 99 8 Mobile broadband subscriptions (per 100 people) — 5.6a 14.3a 11.6a Mobile broadband (% of total mobile subscriptions) — 5.1a 15.4a 14.4a 6 Usage 4 Households with a mobile telephone (%) 70 90 84 83 Mobile voice usage (minutes per user per month) 493 321a 325a 367a 2 Population using mobile Internet (%) 2.1 13.7a 22.9a 22.4a Short Message Service (SMS) users (% of mobile users) — — 74.4a 84.0a 0 2005 2006 2007 2008 2009 2010 Affordability Thailand Mobile basket (% of GNI per capita) 6.5 2.5 2.9 5.7 East Asia & Pacific Region Timor-Leste Lower-middle- East Asia & Timor-Leste income group Pacific Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 1 1 2,519 1,962 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 730 2,220 1,623 3,696 150 Rural population (% of total) 74 72 61 54 120 Expected years of schooling (years) 11 11 10 12 Physicians density (per 1,000 people) 0.1 — 0.8 1.2 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — — 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 2005 2007 2009 2011 Sector performance Timor-Leste East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 3 32 78a 83a Mobile cellular subscriptions (% prepaid) 96 98a 96a 85a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 50 69 86 99 10 Mobile broadband subscriptions (per 100 people) — — 7.3a 11.6a Mobile broadband (% of total mobile subscriptions) — — 9.0a 14.4a 8 Usage 6 Households with a mobile telephone (%) — — 77 83 4 Mobile voice usage (minutes per user per month) 97 87 276a 367a 2 Population using mobile Internet (%) — — 2.9 22.4a Short Message Service (SMS) users (% of mobile users) — — 61.9a 84.0a 0 2005 2006 2007 2008 2009 2010 Affordability Timor-Leste (––) Mobile basket (% of GNI per capita) — 8.7 7.2 5.7 East Asia & Pacific Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 207 World Bank • Mobile at a Glance Togo Low-income Sub-Saharan Togo group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 5 6 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 340 490 530 1,188 80 Rural population (% of total) 60 57 72 63 Expected years of schooling (years) 10 — 9 9 60 Physicians density (per 1,000 people) 0.04 0.05 0.2 0.2 Depositors with commercial banks (per 1,000 adults) 53 181 — 167 40 Sector structure 20 Number of mobile operators — 2 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 6,100 0 2005 2007 2009 2011 Sector performance Togo Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 8 41 43a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 99a 98a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 85 — — 72 120 Mobile broadband subscriptions (per 100 people) — — — 5.6a 100 Mobile broadband (% of total mobile subscriptions) — — — 10.1a 80 Usage 60 Households with a mobile telephone (%) 22 — 43 52 Mobile voice usage (minutes per user per month) — 33 — — 40 Population using mobile Internet (%) — — — — 20 Short Message Service (SMS) users (% of mobile users) — — — — 0 2005 2006 2007 2008 2009 2010 Affordability Togo Mobile basket (% of GNI per capita) 103.4 48.7 28.8 19.5 Sub-Saharan Africa Region Trinidad and Tobago High-income Trinidad and Tobago group 2005 2010 2010 Economic and social context Population (total, million) 1 1 1,127 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 10,880 15,380 38,746 150 Rural population (% of total) 88 86 22 120 Expected years of schooling (years) 11 — 16 Physicians density (per 1,000 people) 1.2 — 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,003 2005 2007 2009 2011 Trinidad and Tobago Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 70 134a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 88 89a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 1.8 Mobile broadband subscriptions (per 100 people) — — 69.6a 1.5 Mobile broadband (% of total mobile subscriptions) — — 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 60 — 93 Mobile voice usage (minutes per user per month) — — 339 0.6 Population using mobile Internet (%) — — 24.3 0.3 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability Trinidad and Tobago Mobile basket (% of GNI per capita) 1.6 0.9 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 208 Information and Communications for Development 2012 World Bank • Mobile at a Glance Tunisia Middle East & Upper-middle- North Africa Tunisia income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 10 11 2,452 331 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 3,200 4,160 5,886 3,874 150 Rural population (% of total) 35 33 43 42 Expected years of schooling (years) 14 14 13 12 120 Physicians density (per 1,000 people) 1.3 1.2 1.7 1.4 90 Depositors with commercial banks (per 1,000 adults) — — — 443 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,497 2005 2007 2009 2011 Tunisia Sector performance Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 57 106a 92a 89a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 98a 81a 87a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 98 100 99 — 10 Mobile broadband subscriptions (per 100 people) — 2.3a 14.3a — 8 Mobile broadband (% of total mobile subscriptions) — 1.9a 15.4a — Usage 6 Households with a mobile telephone (%) — — 84 — 4 Mobile voice usage (minutes per user per month) — 171 325a — Population using mobile Internet (%) — — 22.9a 4.5 2 Short Message Service (SMS) users (% of mobile users) — — 4.4a — 0 Affordability 2005 2006 2007 2008 2009 2010 Tunisia Mobile basket (% of GNI per capita) 4.3 2.9 2.9 3.6 Middle East & North Africa Region Turkey Europe & Upper-middle- Central Asia Turkey income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 68 73 2,452 405 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 6,480 9,890 5,886 7,272 150 Rural population (% of total) 33 30 43 36 Expected years of schooling (years) 11 12 13 13 120 Physicians density (per 1,000 people) 1.3 1.5 1.7 3.2 90 Depositors with commercial banks (per 1,000 adults) 1,362 1,265 — 894 60 Sector structure 30 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,020 2005 2007 2009 2011 Turkey Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 64 88a 92a 125a Mobile cellular subscriptions (% prepaid) 80 65a 81a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 96 100 99 96 12 Mobile broadband subscriptions (per 100 people) — 38.4a 14.3a 22.6a 10 Mobile broadband (% of total mobile subscriptions) — 43.3a 15.4a 18.0a 8 Usage 6 Households with a mobile telephone (%) 73 91 84 82 4 Mobile voice usage (minutes per user per month) 70 261a 325a 288a Population using mobile Internet (%) 0.1 12.2a 22.9a 8.5 2 Short Message Service (SMS) users (% of mobile users) — 64.0a 74.4a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Turkey Mobile basket (% of GNI per capita) 7.3 5.3 2.9 3.1 Europe & Central Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 209 World Bank • Mobile at a Glance Turkmenistan Europe & Lower-middle- Central Asia Turkmenistan income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 5 5 2,519 405 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,650 3,790 1,623 7,272 150 Rural population (% of total) 53 51 61 36 120 Expected years of schooling (years) — — 10 13 Physicians density (per 1,000 people) 2.5 2.4 0.8 3.2 90 Depositors with commercial banks (per 1,000 adults) — — — 894 60 Sector structure 30 Number of mobile operators — 2 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 6,622 2005 2007 2009 2011 Turkmenistan Sector performance Europe & Central Asia Region Access a a Mobile cellular subscriptions (per 100 people) 2 62 78 125 Mobile cellular subscriptions (% prepaid) 89 95a 96a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 14 — 86 96 12 Mobile broadband subscriptions (per 100 people) — — 7.3a 22.6a 10 Mobile broadband (% of total mobile subscriptions) — — 9.0a 18.0a 8 Usage 6 Households with a mobile telephone (%) — — 77 82 4 Mobile voice usage (minutes per user per month) 256 292 276a 288a Population using mobile Internet (%) — — 2.9 8.5 2 Short Message Service (SMS) users (% of mobile users) — — 61.9a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Turkmenistan (—) Mobile basket (% of GNI per capita) — — 7.2 3.1 Europe & Central Asia Region Uganda Low-income Sub-Saharan Uganda group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 28 33 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 300 500 530 1,188 80 Rural population (% of total) 88 87 72 63 Expected years of schooling (years) 10 11 9 9 60 Physicians density (per 1,000 people) 0.1 — 0.2 0.2 40 Depositors with commercial banks (per 1,000 adults) 97 192 — 167 Sector structure 20 Number of mobile operators — 5 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,384 2005 2007 2009 2011 Uganda Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 5 43a 43a 57a Mobile cellular subscriptions (% prepaid) 99 99a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 70 100 — 72 70 Mobile broadband subscriptions (per 100 people) — 1.1a — 5.6a 60 Mobile broadband (% of total mobile subscriptions) — 2.7a — 10.1a 50 Usage 40 Households with a mobile telephone (%) 10 52 43 52 30 Mobile voice usage (minutes per user per month) — 67a — — 20 Population using mobile Internet (%) — — — — 10 0 Short Message Service (SMS) users (% of mobile users) — — — — 2005 2006 2007 2008 2009 2010 Affordability Uganda Mobile basket (% of GNI per capita) 57.6 29.3 28.8 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 210 Information and Communications for Development 2012 World Bank • Mobile at a Glance Ukraine Europe & Lower-middle- Central Asia Ukraine income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 47 46 2,519 405 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,540 3,000 1,623 7,272 150 Rural population (% of total) 32 32 61 36 Expected years of schooling (years) 14 15 10 13 120 Physicians density (per 1,000 people) 3.1 3.2 0.8 3.2 90 Depositors with commercial banks (per 1,000 adults) 2,708 3,220 — 894 60 Sector structure 30 Number of mobile operators — 4 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 4,063 0 2005 2007 2009 2011 Sector performance Ukraine Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 64 118a 78a 125a Mobile cellular subscriptions (% prepaid) 92 92a 96a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 96 100 86 96 18 Mobile broadband subscriptions (per 100 people) 0.0 5.8a 7.3a 22.6a 15 Mobile broadband (% of total mobile subscriptions) 0.1 4.7a 9.0a 18.0a 12 Usage 9 Households with a mobile telephone (%) 44 84 77 82 Mobile voice usage (minutes per user per month) 113 469a 276a 288a 6 Population using mobile Internet (%) — 2.4 2.9 8.5 3 Short Message Service (SMS) users (% of mobile users) — 72.0a 61.9a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Ukraine Mobile basket (% of GNI per capita) 13.5 3.0 7.2 3.1 Europe & Central Asia Region United Arab Emirates High-income United Arab Emirates group 2005 2010 2010 Economic and social context Population (total, million) 4 8 1,127 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 42,280 41,930 38,746 180 Rural population (% of total) 22 22 22 150 Expected years of schooling (years) 11 13 16 Physicians density (per 1,000 people) 1.5 — 2.8 120 Depositors with commercial banks (per 1,000 adults) — — — 90 60 Sector structure 30 Number of mobile operators — 2 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,887 0 2005 2007 2009 2011 United Arab Emirates Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 111 149a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 89 89a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 100 1.4 Mobile broadband subscriptions (per 100 people) 4.1 74.8a 69.6a 1.2 Mobile broadband (% of total mobile subscriptions) 3.7 45.4a 57.6a 1.0 Usage 0.8 Households with a mobile telephone (%) 95 97 93 0.6 Mobile voice usage (minutes per user per month) — — 339 0.4 Population using mobile Internet (%) 4.9 9.3 24.3 0.2 Short Message Service (SMS) users (% of mobile users) — — 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability United Arab Emirates Mobile basket (% of GNI per capita) 0.2 0.3 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 211 World Bank • Mobile at a Glance United Kingdom High-income United Kingdom group 2005 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 60 62 1,127 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 38,850 38,200 38,746 150 Rural population (% of total) 10 10 22 120 Expected years of schooling (years) 17 16 16 Physicians density (per 1,000 people) 2.2 2.7 2.8 90 Depositors with commercial banks (per 1,000 adults) — — — 60 Sector structure 30 Number of mobile operators — 4 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,495 2005 2007 2009 2011 United Kingdom Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 109 130a 118a Mobile cellular subscriptions (% prepaid) 67 50a 36a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 100 1.5 Mobile broadband subscriptions (per 100 people) 7.7 67.5a 69.6a Mobile broadband (% of total mobile subscriptions) 6.9 55.2a 57.6a 1.2 Usage 0.9 Households with a mobile telephone (%) 88 93 93 0.6 Mobile voice usage (minutes per user per month) 151 192a 339 0.3 Population using mobile Internet (%) 9.3 20.2 24.3 Short Message Service (SMS) users (% of mobile users) 83.5 90.3 78.2a 0.0 2005 2006 2007 2008 2009 2010 Affordability United Kingdom Mobile basket (% of GNI per capita) 1.1 1.0 1.0 High-income group United States High-income United States group 2005 2010 2010 Economic and social context Population (total, million) 296 309 1,127 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 44,660 47,340 38,746 150 Rural population (% of total) 19 18 22 120 Expected years of schooling (years) 16 16 16 Physicians density (per 1,000 people) 2.7 2.4 2.8 90 Depositors with commercial banks (per 1,000 adults) 337 — — 60 Sector structure 30 Number of mobile operators — 4 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,848 0 2005 2007 2009 2011 United States Sector performance High-income group Access Mobile cellular subscriptions (per 100 people) 70 106a 118a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 11 16a 36a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 99 100 100 1.5 Mobile broadband subscriptions (per 100 people) 2.1 72.8a 69.6a 1.2 Mobile broadband (% of total mobile subscriptions) 3.0 67.0a 57.6a 0.9 Usage Households with a mobile telephone (%) 51 85 93 0.6 Mobile voice usage (minutes per user per month) 683 772 339 0.3 Population using mobile Internet (%) 6.6 35.6a 24.3 Short Message Service (SMS) users (% of mobile users) — 68.0 78.2a 0 2005 2006 2007 2008 2009 2010 Affordability United States Mobile basket (% of GNI per capita) 0.5 0.8 1.0 High-income group Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 212 Information and Communications for Development 2012 World Bank • Mobile at a Glance Uruguay Latin America & Upper-middle- the Caribbean Uruguay income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 3 3 2,452 583 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 4,740 10,230 5,886 7,741 150 Rural population (% of total) 8 8 43 21 120 Expected years of schooling (years) 15 16 13 14 Physicians density (per 1,000 people) 4.2 3.7 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) 341 538 — — 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,746 0 2005 2007 2009 2011 Sector performance Uruguay Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 35 136a 92a 109a Mobile cellular subscriptions (% prepaid) 85 71a 81a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 100 100 99 98 7 Mobile broadband subscriptions (per 100 people) — 21.7a 14.3a 16.1a 6 Mobile broadband (% of total mobile subscriptions) — 15.4a 15.4a 15.2a 5 Usage 4 Households with a mobile telephone (%) 35 83 84 84 3 Mobile voice usage (minutes per user per month) — — 325a 141a 2 Population using mobile Internet (%) — 4.8 22.9a 4.4 1 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Uruguay Mobile basket (% of GNI per capita) 6.3 2.1 2.9 3.7 Latin America & the Caribbean Region Uzbekistan Europe & Lower-middle- Central Asia Uzbekistan income group Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 26 28 2,519 405 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 530 1,280 1,623 7,272 150 Rural population (% of total) 63 63 61 36 120 Expected years of schooling (years) 12 11 10 13 Physicians density (per 1,000 people) 2.7 2.6 0.8 3.2 90 Depositors with commercial banks (per 1,000 adults) 676 957 — 894 60 Sector structure 30 Number of mobile operators — 5 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,339 0 2005 2007 2009 2011 Uzbekistan Sector performance Europe & Central Asia Region Access Mobile cellular subscriptions (per 100 people) 3 84a 78a 125a Mobile cellular subscriptions (% prepaid) 90 95a 96a 82a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 75 93 86 96 20 Mobile broadband subscriptions (per 100 people) — 6.6a 7.3a 22.6a Mobile broadband (% of total mobile subscriptions) — 8.1a 9.0a 18.0a 15 Usage 10 Households with a mobile telephone (%) 50 87 77 82 Mobile voice usage (minutes per user per month) 450 389a 276a 288a 5 Population using mobile Internet (%) — 0.7 2.9 8.5 Short Message Service (SMS) users (% of mobile users) — 25.0 61.9a 69.8a 0 2005 2006 2007 2008 2009 2010 Affordability Uzbekistan Mobile basket (% of GNI per capita) 18.3 2.8 7.2 3.1 Europe & Central Asia Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 213 World Bank • Mobile at a Glance Venezuela, RB Latin America & Upper-middle- the Caribbean Venezuela, RB income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 27 29 2,452 583 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 4,950 11,590 5,886 7,741 150 Rural population (% of total) 8 6 43 21 Expected years of schooling (years) 12 14 13 14 120 Physicians density (per 1,000 people) — — 1.7 1.8 90 Depositors with commercial banks (per 1,000 adults) — — — — 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 0 2005 2007 2009 2011 Venezuela, RB Sector performance Latin America & the Caribbean Region Access Mobile cellular subscriptions (per 100 people) 47 98a 92a 109a Mobile cellular subscriptions (% prepaid) 95 94a 81a 81a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 85 — 99 98 7 Mobile broadband subscriptions (per 100 people) 0.3 26.1a 14.3a 16.1a 6 Mobile broadband (% of total mobile subscriptions) 0.5 24.7a 15.4a 15.2a 5 Usage 4 Households with a mobile telephone (%) 26 46 84 84 3 Mobile voice usage (minutes per user per month) 116 — 325a 141a 2 Population using mobile Internet (%) — 5.5 22.9a 4.4 1 Short Message Service (SMS) users (% of mobile users) — — 74.4a — 0 2005 2006 2007 2008 2009 2010 Affordability Venezuela, RB Mobile basket (% of GNI per capita) 5.5 2.3 2.9 3.7 Latin America & the Caribbean Region Vietnam Lower-middle- East Asia & Vietnam income group Pacific Region 2005 2010 2010 2010 Economic and social context Population (total, million) 82 87 2,519 1,962 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 630 1,160 1,623 3,696 200 Rural population (% of total) 74 71 61 54 Expected years of schooling (years) — — 10 12 150 Physicians density (per 1,000 people) — 1.2 0.8 1.2 Depositors with commercial banks (per 1,000 adults) — — — — 100 Sector structure 50 Number of mobile operators — 7 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 2,664 2005 2007 2009 2011 Vietnam Sector performance East Asia & Pacific Region Access Mobile cellular subscriptions (per 100 people) 12 134a 78a 83a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 92 88a 96a 85a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 70 — 86 99 25 Mobile broadband subscriptions (per 100 people) 0.01 25.6a 7.3a 11.6a 20 Mobile broadband (% of total mobile subscriptions) 0.03 16.4a 9.0a 14.4a Usage 15 Households with a mobile telephone (%) 30 50 77 83 10 Mobile voice usage (minutes per user per month) — — 276a 367a 5 Population using mobile Internet (%) — 8.2 2.9 22.4a Short Message Service (SMS) users (% of mobile users) — 49.0 61.9a 84.0a 0 2005 2006 2007 2008 2009 2010 Affordability Vietnam Mobile basket (% of GNI per capita) 19.1 5.6 7.2 5.7 East Asia & Pacific Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 214 Information and Communications for Development 2012 World Bank • Mobile at a Glance West Bank and Gaza Middle East & Lower-middle- North Africa West Bank and Gaza income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 4 4 2,519 331 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 1,250 — 1,623 3,874 150 Rural population (% of total) 28 28 61 42 Expected years of schooling (years) 13 13 10 12 120 Physicians density (per 1,000 people) — — 0.8 1.4 90 Depositors with commercial banks (per 1,000 adults) — 543 — 443 60 Sector structure 30 Number of mobile operators — 2 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 6,800 0 2005 2007 2009 2011 West Bank and Gaza Sector performance Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 16 45 78a 89a Mobile cellular subscriptions (% prepaid) 90 90a 96a 87a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 95 — 86 — 25 Mobile broadband subscriptions (per 100 people) — — 7.3a — Mobile broadband (% of total mobile subscriptions) — — 9.0a — 20 Usage 15 Households with a mobile telephone (%) 37 92 77 — 10 Mobile voice usage (minutes per user per month) — — 276a — 5 Population using mobile Internet (%) — — 2.9 4.5 Short Message Service (SMS) users (% of mobile users) — 94.0 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability West Bank and Gaza Mobile basket (% of GNI per capita) 23.2 — 7.2 3.6 Middle East & North Africa Region Yemen, Rep. Middle East & Lower-middle- North Africa Yemen, Rep. income group Region 2005 2010 2010 2010 Economic and social context Population (total, million) 21 24 2,519 331 Mobile cellular subscriptions, 2005–11 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 690 1,170 1,623 3,874 150 Rural population (% of total) 71 68 61 42 120 Expected years of schooling (years) 9 — 10 12 Physicians density (per 1,000 people) 0.3 0.3 0.8 1.4 90 Depositors with commercial banks (per 1,000 adults) 54 101 — 443 60 Sector structure 30 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 3,450 0 2005 2007 2009 2011 Sector performance Yemen, Rep. Middle East & North Africa Region Access Mobile cellular subscriptions (per 100 people) 11 36a 78a 89a Mobile cellular subscriptions (% prepaid) 92 87a 96a 87a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 68 84 86 — 25 Mobile broadband subscriptions (per 100 people) — — 7.3a — Mobile broadband (% of total mobile subscriptions) — — 9.0a — 20 Usage 15 Households with a mobile telephone (%) — — 77 — 10 Mobile voice usage (minutes per user per month) — — 276a — 5 Population using mobile Internet (%) — — 2.9 4.5 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Yemen, Rep. Mobile basket (% of GNI per capita) 20.1 8.3 7.2 3.6 Middle East & North Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. Information and Communications for Development 2012 215 World Bank • Mobile at a Glance Zambia Lower-middle- Sub-Saharan Zambia income group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 11 13 2,519 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 500 1,070 1,623 1,188 80 Rural population (% of total) 65 64 61 63 Expected years of schooling (years) — — 10 9 60 Physicians density (per 1,000 people) 0.1 — 0.8 0.2 40 Depositors with commercial banks (per 1,000 adults) — — — 167 Sector structure 20 Number of mobile operators — 3 0 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — 5,478 2005 2007 2009 2011 Zambia Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 8 54a 78a 57a Mobile basket, 2005–10 Mobile cellular subscriptions (% prepaid) 99 99a 96a 96a Percentage of GNI per capita Population covered by a mobile-cellular network (%) 65 90 86 72 60 Mobile broadband subscriptions (per 100 people) — 0.3a 7.3a 5.6a 50 Mobile broadband (% of total mobile subscriptions) — 0.5a 9.0a 10.1a 40 Usage 30 Households with a mobile telephone (%) 15 58 77 52 Mobile voice usage (minutes per user per month) — — 276a — 20 Population using mobile Internet (%) — 2.8 2.9 — 10 Short Message Service (SMS) users (% of mobile users) — — 61.9a — 0 2005 2006 2007 2008 2009 2010 Affordability Zambia Mobile basket (% of GNI per capita) 51.0 19.0 7.2 19.5 Sub-Saharan Africa Region Zimbabwe Low-income Sub-Saharan Zimbabwe group Africa Region 2005 2010 2010 2010 Economic and social context Mobile cellular subscriptions, 2005–11 Population (total, million) 13 13 796 853 Number per 100 people GNI per capita, World Bank Atlas method (current US$) 440 460 530 1,188 80 Rural population (% of total) 64 62 72 63 Expected years of schooling (years) — — 9 9 60 Physicians density (per 1,000 people) 0.2 — 0.2 0.2 Depositors with commercial banks (per 1,000 adults) — — — 167 40 Sector structure 20 Number of mobile operators — 3 Herfindahl-Hirschman Index (HHI) (scale = 0–10,000) — — 0 2005 2007 2009 2011 Zimbabwe Sector performance Sub-Saharan Africa Region Access Mobile cellular subscriptions (per 100 people) 5 60 43a 57a Mobile cellular subscriptions (% prepaid) 87 93a 98a 96a Mobile basket, 2005–10 Percentage of GNI per capita Population covered by a mobile-cellular network (%) 70 80 — 72 70 Mobile broadband subscriptions (per 100 people) — 8.6a — 5.6a 60 Mobile broadband (% of total mobile subscriptions) — 12.4a — 0.1a 50 Usage 40 Households with a mobile telephone (%) 10 54 43 52 30 Mobile voice usage (minutes per user per month) 119 98 — — 20 Population using mobile Internet (%) — 0.6 — — 10 Short Message Service (SMS) users (% of mobile users) — 47.0 — — 0 2005 2006 2007 2008 2009 2010 Affordability Zimbabwe Mobile basket (% of GNI per capita) 16.4 53.5 28.8 19.5 Sub-Saharan Africa Region Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years or periods other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. 216 Information and Communications for Development 2012 World Bank • Mobile at a Glance Key mobile indicators for other economies, 2010 GNI per capita, Mobile cellular Population covered Mobile cellular Population World Bank Atlas subscriptions by a mobile-cellular Number of mobile basket (% of GNI (total, thousand) method (current US$) (per 100 people) network (%) operators per capita) 2010 2010 2010 2010 2010 2010 Afghanistan 34,385 410 39a 75 4 — American Samoa 68 —b — — — — Andorra 85 41,750 77 99 — — Antigua and Barbuda 88 13,280 186 100 3 2.0 c Aruba 108 — 122 99 — — Bahamas, The 343 22,240 125 100 1 0.9 Barbados 274 12,660 128 100 2 1.0 Belize 345 3,810 56 — 1 9.8 c Bermuda 65 — 137 — 3 — Bhutan 726 1,870 52 100 2 2.9 Brunei Darussalam 399 31,800 109a — 2 — Cape Verde 496 3,270 75 85 2 15.3 c Cayman Islands 56 — 178 100 — — Channel Islands 153 67,960 — — — — a Comoros 735 750 32 — 1 38.8 c Curaçao 143 — — — — — a Djibouti 889 1,270 23 90 1 6.2 Dominica 68 6,740 147 90 2 2.6 Equatorial Guinea 700 14,550 58 — 2 — c Faeroe Islands 49 — 122 100 — — Fiji 860 3,630 81 65 2 6.2 French Polynesia 271 —c 80 80 1 — c Gibraltar 29 — 103 — — — Greenland 57 26,020 101 100 — — Grenada 104 6,960 112 — 2 2.5 Guam 179 —c — — — — Guyana 755 2,870 74 95 2 3.9 Iceland 318 32,640 118 99 4 0.6 Isle of Man 83 48,910 — — — — Kiribati 100 2,000 10 — 1 10.4 Korea, Dem. People’s Rep. 24,346 —d 3a — 1 — Kosovo 1,815 3,290 86 — 2 — a Liberia 3,994 200 41 — 4 — Liechtenstein 36 137,070 80 95 — — Luxembourg 507 76,980 143 100 3 0.4 Macao SAR, China 544 34,880 206 100 3 0.1 Maldives 316 5,750 156 100 2 1.2 (continued next page) Information and Communications for Development 2012 217 World Bank • Mobile at a Glance Key mobile indicators continued GNI per capita, Mobile cellular Population covered Mobile cellular Population World Bank Atlas subscriptions by a mobile-cellular Number of mobile basket (% of GNI (total, thousand) method (current US$) (per 100 people) network operators per capita) 2010 2010 2010 2010 2010 2010 Malta 416 19,130 109 100 3 1.4 Marshall Islands 54 3,640 7 — — — b Mayotte 204 — — — — — Micronesia, Fed. Sts. 111 2,740 25 — 1 4.0 Monaco 35 183,150 — — — — a Montenegro 632 6,740 183 100 — 2.9 c New Caledonia 247 — 89 89 — — c Northern Mariana Islands 61 — — — 2 — Palau 20 6,560 71 95 — — Samoa 184 2,980 91 — 2 7.1 San Marino 32 50,400 76 98 — — S~ ao Tomé and Principe 165 1,200 62 88 1 12.7 Seychelles 87 9,710 146 98 3 2.0 c Sint Maarten (Dutch part) 38 — — — — — a Solomon Islands 538 1,030 33 — 2 — d Somalia 9,331 — 34a — — — South Sudan 9,948f —e 24 — 5 — St. Kitts and Nevis 52 11,830 154 — 2 1.5 St. Lucia 174 6,560 113 100 2 4.1 c St. Martin (French part) 30 — — — — — St. Vincent and the Grenadines 109 6,320 113 100 2 2.8 Suriname 525 5,920 170 — 3 1.9 Tonga 104 3,290 52 90 2 4.0 c Turks and Caicos Islands 38 — — — — — Tuvalu 10 4,760 25 — — — Vanuatu 240 2,640 27 — 2 10.6 c Virgin Islands (U.S.) 110 — — — — — Sources: Economic and social context: IMF, UIS, UN, WHO and World Bank; Sector structure: ictDATA.org; Sector performance: ictDATA.org, ITU; Wireless Intelligence, and World Bank. Notes: Use of italics in the column entries indicates years other than those specified. — Not available. GNI = gross national income. a. Data are for 2011. b. Estimated to be upper middle income ($3,976–$12,275). c. Estimated to be high income ($12,276 or more). d. Estimated to be low income ($1,005 or less). e. Estimated to be lower middle income ($1,006–$3,975). f. 2010 estimate. 218 Information and Communications for Development 2012 Contributors Maja Andjelkovic is interested in the potential of the Finance. Before joining the World Bank, he worked for the mobile industry to create opportunities in emerging U.K. Department for International Development (DFID) markets and in the role of mobile technology in human and the European Commission. Mr. Fantom studied statistics development. With the World Bank’s Information for and mathematics in the United Kingdom, at University Development Program (infoDev), she works on support- College London, the University of Oxford, and the University ing entrepreneurs to establish businesses in Africa, Asia, of Durham. and Europe. During LLM studies at the University of Kent, she examined public-private governance of the Nicolas Friederici is a consultant at infoDev at the World internet. As a PhD student at Oxford University’s Internet Bank. His research interests cover ICT for development and Institute, she is focusing on social aspects of innovation mobile innovation. He has authored academic publications in the context of mobile entrepreneurship. in the fields of broadband economics and policy, social online behavior, and knowledge management. He is also Kevin Donovan is a research associate in the World Bank’s involved in infoDev’s operational work in mobile innovation infoDev. He graduated from Georgetown University’s School and incubation. He was a Fulbright scholar at Michigan of Foreign Service with a degree in science, technology, and State University where he received a master’s degree in international affairs and spent part of 2012 as a Fulbright telecommunication, information studies, and media. He also recipient studying the intersection of digital technology and holds a Diplom in media studies and media management democratic engagement in South Africa. He previously from the University of Cologne. served on the board of directors of Students for Free Culture, an international NGO working to reform intellec- Naomi J. Halewood is an ICT policy specialist with the ICT tual property rights, and managed Georgetown’s Open- Unit of the World Bank, where she works on projects involv- CourseWare initiative. ing telecommunications sector development and moderniz- ing government through the use of ICT, mainly in the East Neil Fantom is a manager in the Development Economics Asia and Pacific Region. Her contributions to publications Data Group of the World Bank. He leads the team that examine the role of ICT and, more recently, the mobile provides open access to the World Bank’s databases on devel- phone in various development contexts such as agriculture, opment and manages the compilation and publication of the public service delivery, and small and medium enterprise World Development Indicators and Global Development development. Before joining the ICT Unit, she worked in the 219 Development Economics Data Group of the World Bank. Buyant Erdene Khaltarkhuu is a statistical analyst in the She holds master’s degrees in international development and Development Economics Data Group of the World Bank. business administration from American University and a She is an author and producer of the States and Markets bachelor’s degree in political science and sociology from section of the World Development Indicators database and Brandeis University. publication, responsible for data and statistics on topics such as the private sector, the financial system, governance, trans- Carol Hullin specializes in health informatics. She works as port, ICT, and science and technology. She has a master’s a professor of health informatics in developing countries degree in economics from Northern Illinois University. such as Argentina, Bolivia, and Chile. As a consultant to the World Bank’s ICT Sector Unit, she works on the eHealth Kaoru Kimura is an operations analyst with the ICT Sector strategy. Her areas of expertise include ICT for health, Unit at the World Bank Group. She has worked on several education, and social development, with an emphasis in operational and analytical projects in Sub-Saharan Africa policy-making and utilization of mobile technologies. She and East Asia. In addition, she has been actively involved in has a PhD in health informatics from Melbourne University, monitoring and evaluation activities in the ICT sector. She Australia. Currently, she is the vice president of the Latino has worked on the ICT at-a-glance tables, Core Sector Indi- American and Caribbean Federation of Medical Informat- cators, and the Little Data Book on Information and Commu- ics, and a founder of the Chilean and Peruvian Health Infor- nication Technology series. Before joining the ICT Sector matics Association, an NGO within the International Unit, she worked at Nippon Telegraph and Telecommunica- Medical Informatics Association in Geneva, Switzerland. tion in Japan. She has a master’s degree in international development studies from the National Graduate Institute Saori Imaizumi is a consultant in the World Bank’s educa- for Policy Studies in Japan. tion team in the South Asia Region. She specializes in skills development, engineering education, and ICT and educa- Soong Sup Lee is a senior information officer in the Devel- tion, conducting operational and analytical work in India opment Economics Data Group of the World Bank. He is a and Pakistan. With her background as an IT/management member of the team that provides open access to the World consultant in the private sector, she actively leverages busi- Bank’s databases and leads the team that produces the World ness acumen and technologies to help solve issues in an Development Indicators database and publication. Mr. Lee innovative way, especially in the education sector. Her work has worked in various roles at the World Bank for over 25 includes the use of mobile phone for a tracer study and use years. His current focus is improving the access and useful- of ICT in teacher education and monitoring and evaluation. ness of the World Bank’s information for a broad audience. She holds a master’s degree in development economics and Mr. Lee has a master’s degree in business administration international business from the Fletcher School at Tufts from George Washington University and a bachelor’s degree University and a bachelor’s degree in comparative politics in engineering from McGill University. and international relations from Wesleyan University. Samia Melhem is the chair of the e-Development Thematic Tim Kelly acted as Task Team Leader and led the research Group. Her current operational and analytical responsibili- and drafting of this report. He is a lead ICT policy specialist ties include technical assistance, planning, and supervision working with the ICT Sector Unit and infoDev within the of eGoverment operations. In her 20 years of experience in World Bank Group. He previously worked at the Interna- development at the World Bank Group, Ms. Melhem has tional Telecommunication Union (ITU) and Organisation worked on ICT4D in several sectors: telecoms policy regu- for Economic Co-operation and Development (OECD). He lation, ICT for public sector reform (taxes, customs, trade), is the author or co-author of more than 30 books in the field education, the knowledge economy, and private sector of ICT4D, including the OECD Communications Outlook development. She has held several positions in different and the ITU Internet Reports. At the Bank, he is co-author of regions such as Africa, the Middle East, and Europe and the Broadband Strategies Handbook. He holds a PhD in geog- Central Asia. She is the sector coordinator for governance raphy from the University of Cambridge, U.K. and accountability, and gender. She holds degrees in 220 Contributors electrical engineering (BS), computer sciences (MS), and in business administration in decision analysis from Arizona finance (MBA). State University. Michael Minges is an independent consultant with more Siddhartha Raja is a policy specialist with the ICT Sector Unit than 20 years of experience advising governments and the of the World Bank Group. He works with governments in private sector on ICT issues in developing countries. He South Asia, Eastern Europe, and Central Asia on ICT sector previously worked for Telecommunications Management strategy and telecommunications policy development and Group (TMG) where he was senior market analyst. Before provides advisory services on using mobile tools to support joining TMG, he served as head of the Markets, Economics service delivery and good governance. He has published books and Finance Unit at the International Telecommunication on media convergence and broadband telecommunications Union (ITU). While at the ITU he launched the World during his time with the World Bank. Mr. Raja has a bache- Telecommunications Development Report, a principal indus- lor’s degree in telecommunications engineering from the try publication, and designed the Digital Access Index for University of Bombay, a master’s degree in infrastructure measuring ICT progress. He also worked at the International policy studies from Stanford University, and a doctorate in Monetary Fund as an information technology specialist. telecommunications policy from the University of Illinois. Mr. Minges holds an MBA in information systems from George Washington University. Priya Surya is a technology consultant in the World Bank’s South Asia Rural Livelihoods Unit, where she works on strat- Victor Mulas is an ICT policy specialist in the World Bank’s egy and implementation of mobile, smartcard, big data, and ICT Sector Unit. His expertise lies in policy analysis and multimedia technologies for improving livelihood outcomes advisory work on sector reform, policy strategy, regulatory and public service delivery. Her work focuses on driving frameworks, ICT-led innovation and transformation, and customer adoption and improving the user experience. Her institutional capacity building. Before coming to the World areas of expertise include financial inclusion, branchless Bank, he worked for Telecommunications Management banking, mobile-based data collection, agricultural value Group, a global consulting firm, for an affiliate of the Tiscali chain, innovative business models, and community-driven group in Spain, and as an associate lawyer for a telecommu- development. She has an MPA in international development nications law firm in Spain. Mr. Mulas holds an MBA with from the Harvard Kennedy School and a BA in economics an International Business Diplomacy certificate from the from Macaulay Honors College at the City University of McDonough School of Business at Georgetown University, New York. an LLM in telecommunications law from Universidad de Comillas, and a law degree from Universidad Autonoma de Masatake Yamamichi is a consultant in the World Bank’s Madrid. ICT Sector Unit. His expertise lies in ICT policies, telecom- munications reform, and eGovernment, and their relevant William Prince is a senior information officer in the Devel- areas, such as ICT-enabled social development and employ- opment Economics Data Group of the World Bank, where he ment. He is also involved in operational work with client leads the Data Administration and Quality team responsible countries in the Middle East and North Africa and the unit’s for production and content management of electronic data global analytical work and portfolio review. He has products, including the online Open Data versions of World contributed to a number of ICT-related publications as an Development Indicators and Global Development Finance. He author, researcher, and reviewer. He holds a bachelor’s also provides overall data management and support for the degree in economics from the University of Tokyo and a Data Group’s clients. Before joining the Bank, he was a statis- master’s degree in international relations from the Maxwell tical consultant for British Telecom. He has a master’s degree School of Syracuse University. Contributors 221 ECO-AUDIT Environmental Benefits Statement The World Bank is committed to preserving Saved: endangered forests and natural resources. • 31 trees The Office of the Publisher has chosen to • 13 million BTU of total print Information and Communications energy for Development 2012: Maximizing • 3.153 pounds of net Mobile on recycled paper with 50 percent greenhouse gases (CO2 postconsumer fiber in accordance with the equivalent) recommended standards for paper usage set • 14,216 gallons of by the Green Press Initiative, a nonprofit waste water program supporting publishers in using • 901 pounds of solid fiber that is not sourced from endangered waste forests. For more information, visit www .greenpressinitiative.org. W ith some six billion mobile subscriptions now in use worldwide, about three-quarters of humanity has access to a mobile phone. Mobiles are arguably the most ubiquitous modern technology—in some developing countries, more people have access to a mobile phone than to clean water, a bank account, or even electricity. And mobile communications now offer major opportunities to advance human development—from providing basic access to education or health information to making cash payments and stimulating citizen involvement in democratic processes. Information and Communications for Development 2012: Maximizing Mobile analyzes the growth and evolution of mobile telephony, including the rise of data-based services delivered to handheld devices through “apps� (applications) and other ways. Summarizing current thinking and seeking to inform the debate on the use of mobile phones to improve livelihoods, the report looks, in par- ticular, at key ecosystem-based applications in agriculture, health, �nancial services, employment, and government, with chapters devoted to each, and explores the consequences of the emerging “app economy� for development. The global conversation is no longer about the phone itself, but about how it is used and the content and applications that it opens up. These apps and “mash-ups� of services, driven by high-speed networks, social networking, online crowdsourcing, and innovation, are helping mobile phones transform lives in developed and developing countries alike. They not only ben- e�t individual users, they also boost the economy as a whole through cascade effects stimulat- ing growth, entrepreneurship, and productivity. Mobile communications promise to do more than just give the developing world a voice—they unlock the genie in the phone, empowering people to make their own choices and decisions. T his report pulls together perspectives from many different stakeholders into a cohesive and com- pelling document on mobile applications for development. It will indeed be a valuable contribu- tion to practitioners, funders, and others who are trying to understand this exciting space. —Heather Thorne, Vice President, Information Solutions, Grameen Foundation ISBN 978-0-8213-8991-1 Korean Trust Fund SKU 18991