Towards an understanding of ICT access and use in Africa

Transcription

1 Towards an understanding of ICT access and use in Africa Dr. Alison Gillwald Executive Director: Research ICT Africa Adjunct Professor - University of Cape Town, GSB, Management of Infrastructure Reform and Regulation Programme 1

2 Basic Content Ubiquity - critical mass - network effects Access Usage Applications Platforms 2

3 Network a response to the research vacuum on the continent in relation to ICT policy and regulation and dearth of capacity to respond to redress it.

4 ICT Ecosystem Integrated perspective of markets, networks, services, services, applications and content and determining governance, legal and regulatory frameworks Global/regional Governance ITU, ICANN, WTO Global players and associations Google, Facebook, GSMA Market Structure (competitiveness) National/industry formations (unions, industry associations, NGOs) Employment Apps Investment Services CLOUD Affordability Users Consumers Citizens Access Networks Policy & Legal Framework State Constitution Innovation Content Human Development (e-skills) Institutional Arrangements (NRA, CC, USF) Multilateral Agencies (WB, AfDB, International Donors Adapted from Gillwald (2012) 4

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6 Table 1 General sample statistics of randomly selected individual Average individual income US $ Average income US$ ppp All All Average age % with a bank account All ,4 52,4 45,6 52% ,9 10,8 10,9 Ethiopia 45% ,7 4,3 3,0 55% ,4 35,5 24,5 ICT Access and Usage 2011 Survey 62% ,5 57,6 36,4 57% ,3 51,1 60,3 47% ,5 39,8 20,0 50% ,3 17,4 15,2 54% ,9 62,7 55,7 54% ,2 7,4 5,1 44% ,2 18,7 10,7

7 23.3$ 16.6$ 9.6$ 21.3$ 14.4$ 19.1$ 17.3$ 15.5$ 13.8$ 16.3$ 12.2$ 16.1$ 9.6$ 16.6$ 22.4$ 28.2$ 4.7$ 16.7$ 20.9$ 7.8$ 4.4$ 4.8$ 9.9$ 7.9$ 10.1$ 12.5$ 10.8$ 14.7$ 4.8$ 11.8$ 7.6$ 6.0$ 31.1$ 35.9$ 27.7$ 10.8$ 34.8$ 3.3$ 16.2$ 4.1$ 15.1$ 5.4$ 14.7$ 26.0$ 27.4$ 47.8$ 39.1$ 25.6$ 58.6$ 22.6$ 47.3$ 45.8$ 49.7$ 41.6$ 9.1$ 7.7$ 5.6$ $ $ $ $ Ethiopia$ $ $ $ $ South$ Africa$ $ share&of&main&ac-vity&engaged&in...& student$/$pupil$ unpaid$work$/$housewife$ reored$ unemployed$ disabled$and$unable$to$work$ employed$ selfpemployed$

8 Table 2 Gender disaggregated educational sample statistics Highest Education: Tertiary Highest Education: Secondary Highest Education: Primary All All All 20,5% 21,9% 19,4% 53,9% 53,9% 54,0% 18,7% 19,3% 18,2% 7,4% 8,6% 6,2% 22,8% 19,2% 26,2% 30,6% 30,7% 30,6% Ethiopia 2,1% 2,4% 1,8% 1,8% 1,3% 2,4% 13,1% 16,4% 8,9% 10,5% 15,8% 6,2% 36,6% 38,9% 34,8% 27,3% 25,3% 28,9% 26,2% 32,7% 22,3% 41,4% 41,1% 41,7% 27,4% 22,8% 30,2% 7,1% 8,4% 6,1% 27,8% 24,3% 30,4% 45,2% 42,4% 47,4% 14,8% 19,5% 9,6% 37,8% 40,3% 34,9% 18,7% 18,1% 19,3% 1,2% 1,7% 0,7% 15,3% 16,8% 13,7% 58,4% 59,4% 57,4% 13,3% 18,0% 9,1% 65,3% 65,8% 64,8% 17,0% 13,2% 20,2% 1,4% 1,5% 1,2% 11,1% 14,9% 7,8% 72,0% 73,3% 70,9% 9,1% 11,2% 6,3% 29,9% 33,3% 25,6% 44,2% 44,6% 43,7%

9 Africa s Digital Divide Household data analysis

10 Percentage of households with electricity still very low in many African countries, some even saw a decline 2007/8 2011/12 89% 73% 77% 46,6% average 45% 42% 58% 48% 60% 47% 60% 57% 65% 63% 13% 10% 5% 16% 18% 19% 13% Ethiopia

11 Radio still main source of information TV luxury good in several countries Households with Radio Households with TV 81% 78% 77% 59% 72% 54% 72% 54% 72% 53% 70% 44% 66% 41% 63% 18% 62% 13% Ethiopia 41% Ethiopia 10% 34% 9% ga

12 Share of households with fixed-lines 2007/8 2011/12 Ethiopia 2,6% 1,8% 2,3% 0,6% 1,8% 2,2% 0,9% 0,4% 0,3% 1,5% 0,1% 0,2% 0,3% 4,0% 7,6% 11,5% 11,0% 15,0% Fixed-lines on the way out except,, and 18,2% 18,0% 17,4% ga

13 Share of households with a working computer Share of households with a working Internet connection 24,5% 19,7% 15,7% 12,7% 14,7% 11,5% Ethiopia 0,7% 12,7% 8,6% 8,5% 6,6% 2,2% 2,0% 1,6% Ethiopia 0,5% 3,4% 2,7% 1,3% 0,9% 0,8% 0,7% 8,6% Less than a quarter of households have a computer and even fewer Internet access ga

14 15+ Owning a mobile 15+ Owning a mobile that is capable of browsing the Internet 84% 51% 80% 32% 74% 31% 66% 30% 60% 29% 56% 23% 47% 19% 45% 19% 36% 15% 24% 15% Ethiopia 18% Ethiopia 7%

15 Individual Access and Usage

16 15+ Owning a mobile Ethiopia 18% 84% 80% 74% 66% 60% 56% 47% 45% 36% 24% Share of those with a mobile that own one that is capable of browsing the Internet Ethiopia 7% 19% 19% 15% 15% 23% 32% 31% 30% 29% 51%

17 sending cash with someone preferred way of sending money Means of sending and receiving money that the business uses Mobile Money Post Office Western Union etc Banks send cash with someone Ethiopia 16% 1% 2% 17% 81% 14% 0% 0% 5% 93% 8% 0% 1% 10% 70% 0% 0% 0% 5% 55% 0% 1% 1% 12% 54% 0% 1% 26% 4% 75% 0% 0% 0% 11% 77% 1% 25% 1% 41% 86% 2% 16% 3% 27% 73% Some mobile money use in East Africa

18 Internet Access & Usage

19 2007/8 2011/12 Ethiopia 1% 2% 2% 2% 6% 3% 4% 6% 8% 13% Internet use (15+) more than doubled within 4 years 9% 13% 14% 16% 18% 15% 26% 6% 29% 15% 34% ga

20 ITU data: Percentage of individuals using the Internet!30!!!25!!!20!!! Ethiopia!!!!!!! Mozambique!! South!Africa!!!15!!!10!!!5!!!"!! 1996! 1997! 1998! 1999! 2000! 2001! 2002! 2003! 2004! 2005! 2006! 2007! 2008! 2009! 2010!

21 Using mobile to browse the Internet 8% 8% 5% Ethiopia 5% 15% 13% 16% 25% 24% 23% Using mobile for Facebook etc. 18% 17% 16% 14% 11% 8% 7% 5% Ethiopia 2% 25% 25% 28% Internet use among mobile phone owners: Social networking more popular than in some countries Using mobile for ing 10% 4% 6% 5% Ethiopia 10% 12% 13% 15% 17% 17% 20%

22 Daily Internet use increased in past 4 years 56% 64% 41% 35% 53% 59% 32% 43% 31% 55% Ethiopia 19% 15% 47% 52% 15% 13% 28% 34% 11% 11% 19% 57% 2007/8 2011/12 ga

23 Where was the Internet used first? Computer Mobile phone Ethiopia 82,1% 70,8% 70,6% 70,5% 68,9% 65,1% 50,1% 45,8% 45,2% 33,3% 17,9% 29,2% 29,4% 29,5% 31,1% 34,9% 49,9% 54,2% 54,8% 66,7% 28,2% 71,8% ga

24 Where the Internet was used in past 12 months Mobile phone Work Place of education Internet cafe 74% 80% 85% 51% 35% 58% 32% 51% 33% 21% 36% 50% 31% 52% 63% 24% 45% 45% 20% 29% 72% 39% 31% 42% 21% 17% 51% 55% 23% 36% 48% 20% 10% 30% 61% 64% 71% 71% 75% 75% 78% 81% 81% 87% Ethiopia ga

25 Internet Access Models Hardware Billing Skill requirement Electricity Location Old Internet Computer / Laptop Postpaid (monthly Internet subscription) High (Windows + Internet explorer + Viruses) electricity mostly required at location of Internet use Work, school, Internet cafe New Internet Mobile Prepaid Low no required at home Anywhere

26 Ethiopia 0,7% 2,7% 2,2% 3,5% 2,0% 2,4% Internet access: 2007/08 VS 2011/12 6,0% 5,6% 5,8% 7,9% 8,8% 2007/8 2011/12 12,7% 13,0% 14,1% Internet access double in three years 16,2% 15,0% 15,0% 18,4% 26,3% 29,0% 33,7% ga

27 Frequency of Internet daily use: 2007/08 VS 2011/ /8 2011/12 56% 64% 35% 41% 53% 59% 32% 31% 43% 55% Ethiopia 19% 15% 47% 52% 15% 13% 28% 34% 11% 57% 11% 19% ga

28 15+ Internet users Signed up for social network with address 88% 97% 61% 94% 81% 90% 81% 88% 63% 86% 50% 81% 59% 80% 81% 79% 73% 78% 75% 66% Ethiopia 41% Ethiopia 59% ga

29 main%reasons%for%using%the%mobile%phone...% Female% Male% Missed%Call/Please%Call%Me%% 86.5%% 85.7%% Sending/receiving%text%% 88.2%% 85.2%% Playing%games% 42.7%% 46.3%% Sending/receiving%money% 34.9%% 27.5%% Browsing%the%Internet% 16.0%% 21.5%% Downloaded%applica8ons% 12.9%% 18.2%% Reading/wri8ng% s% 11.7%% 16.1%%

30 share&of&reasons&why&individuals&do&not&have&a&mobile&phone...& Female% Male% Cannot%afford%it% 83.7%% 81.3%% No%electricity%at%home%to%charge%% 55.8%% 57.7%% My%phone%got%stolen% 18.8%% 21.4%% No%coverage%where%I%live% 16.4%% 19.9%% Don't%have%anyone%to%call% 19.3%% 19.1%% My%phone%is%broken% 8.0%% 7.5%%

31 Mobile/wireless app ecosystem Up to a two line subtitle, generally used to describe the takeaway for the slide Figure 5: Mobile Application Ecosystem 31

32 M-apps ecosystem Mobile Operating Systems such as ios include an application programming interface (API), which is a software specification used as an interface between different software components. For example, the latest version of the Android OS, Jellybean, provides several public APIs that allows developers to integrate their applications with the OS. Platforms allow other software to be built on top. Examples of platforms include Facebook and emerging market social networking platforms such as Mxit in. A platform provides uniform standards and payment mechanisms - these standards are used by developers to develop and sell applications. A platform sits on top of an operating system. Mobile Applications run on mobile phones, either on the operating system or on a platform such as Mxit or Facebook, that themselves run on an operating system like ios, Android or Symbian OS. ios Figure 6: Conceptual framework for business modeling 32

33 Conclusions The mobile is closing the voice and the data gap in Africa First wave of Internet access through PCs and fixed-line /modem dial-up. Mostly through work, school or public access (Internet cafes) Second wave is through mobile phones Easier to use Cheaper equipment compared to computers Prepaid (modem dial-up was postpaid) No electricity at home needed Internet enabled mobile phones, low bandwidth applications, and social networking are the key drivers Mobile Internet reduces the cost of communication: Facebook Zero, whatsapp, Mixit

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