BUILDING THE INFORMATION SOCIETY 2 June From measurement to policy-making: The DOI From measurement to policy-making: The DOI as a policy tool “Digital Transformations in the Information Society” International Telecommunication Union & the London Business School Joint Conference Geneva, Switzerland 2 June 2006 Lilia Perez-Chavolla, Ph.D. ITU Strategy and Policy Unit
BUILDING THE INFORMATION SOCIETY 2 June The DOI as a policy tool Comprehensive statistical framework to monitor the digital divide Frame of reference for comparisons across time With other countries/regions of interest Nationally, to evaluate progress achieved on national ICT goals and impact of particular policy measures Tool for monitoring internal disparities in ICT opportunity, infrastructure and utilisation based on classificatory variables of interest (income, age, gender, etc.)
BUILDING THE INFORMATION SOCIETY 2 June Regional Comparisons Source: ITU World Information Society Report.
BUILDING THE INFORMATION SOCIETY 2 June Developing giants lead the gainers… O = Opportunity I = Infrastructure U = Utilisation Source: ITU World Information Society Report.
BUILDING THE INFORMATION SOCIETY 2 June DOI Results for Africa Source: ITU World Information Society Report. 32 of the 41 countries with DOI scores below 0.2 are in Africa 62 percent of the African countries included in the Index are ranked among the lowest scores for Opportunity, Infrastructure and Utilisation.
TUNISIA MOROCCO SAHARA ALGERIA MAURITANIA MALI NIGER LIBYA CHAD EGYPT SUDAN ETHIOPIA DJIBOUTI ERITREA SOMALIA KENYA TANZANIA DEMOCRATIC (ZAIRE) CENTRAL RWANDA GABON EQUATORIAL ANGOLA CONGO NIGERIA BENIN DTVOIRE SIERRA SENEGAL GHANA THE GUINEA LIBERIA CAMEROON SOUTH AFRICA MALAWI ZAMBIA MOZAMBIQUE MADAGASCAR ZIMBABWE BOTSWANA SWAZILAND LESOTHO NAMIBIA ANGOLA WESTERN UGANDA OF THE CONGO REPUBLIC BURUNDI GUINEA REP. OF TOGO COTE BURKINA GUINEA LEONE GAMBIA BISSAU Walvis Bay SOUTH REPUBLIC AFRICAN THE AFRICA Top 15 (Mauritius, Eq. Guinea, 0.26) Bottom 15 (Chad, Kenya, 0.13) CAPE VERDE SAO TOME & PRINCIPE SEYCHELLES MAURITIUS Highest DOI score: Republic of Korea, 0.79 Africa’s top and bottom 15: DOI Rankings Source: ITU World Information Society Report.
TUNISIA MOROCC O SAHARA ALGERI A MAURITANI A MALI NIGE R LIBY A CHA D EGYPT SUDAN ETHIOPIA DJIBOUTI ERITREA SOMALI A KENYA TANZANIA DEMOCRATIC (ZAIRE) CENTRA L RWANDA GABON EQUATORIAL ANGOLA CONGO NIGERIA BENI N DTVOIRE SIERRA SENEGAL GHAN A THE GUINEA LIBERIA CAMEROON SOUTH AFRICA MALAWI ZAMBIA MOZAMBIQUE MADAGASCAR ZIMBABWE BOTSWANA SWAZILAND LESOTHO NAMIBIA ANGOLA WESTERN UGANDA OF THE CONGO REPUBLIC BURUNDI GUINEA REP. OF TOGO COTE BURKINA GUINEA LEONE GAMBIA BISSAU Walvis Bay SOUTH REPUBLIC AFRICAN THE AFRICA Top 15 (Eq, Guinea, Mauritius, 0.98) Bottom 15 (Chad, Kenya, 0.34) CAPE VERDE SAO TOME & PRINCIPE SEYCHELLES MAURITIUS Highest Opportunity score: Hong Kong, 0.99 Highs and lows in Opportunity Source: ITU World Information Society Report.
TUNISIA MOROCC O SAHARA ALGERI A MAURITANI A MALI NIGE R LIBY A CHA D EGYPT SUDAN ETHIOPIA DJIBOUTI ERITREA SOMALI A KENYA TANZANIA DEMOCRATIC (ZAIRE) CENTRA L RWANDA GABON EQUATORIAL ANGOLA CONGO NIGERIA BENI N DTVOIRE SIERRA SENEGAL GHAN A THE GUINEA LIBERIA CAMEROON SOUTH AFRICA MALAWI ZAMBIA MOZAMBIQUE MADAGASCAR ZIMBABWE BOTSWANA SWAZILAND LESOTHO NAMIBIA ANGOLA WESTERN UGANDA OF THE CONGO REPUBLIC BURUNDI GUINEA REP. OF TOGO COTE BURKINA GUINEA LEONE GAMBIA BISSAU Walvis Bay SOUTH REPUBLIC AFRICAN THE AFRICA Top 15 (Senegal, Mauritius, 0.4) Bottom 15 (Chad, Zambia, 0.01) CAPE VERDE SAO TOME & PRINCIPE SEYCHELLES MAURITIUS Highest Infrastructure score: Denmark, 0.75 In Infrastructure… Source: ITU World Information Society Report.
TUNISIA MOROCCO SAHARA ALGERIA MAURITANIA MALI NIGER LIBYA CHAD EGYPT SUDAN ETHIOPIA DJIBOUTI ERITREA SOMALIA KENYA TANZANIA DEMOCRATIC (ZAIRE) CENTRAL RWANDA GABON EQUATORIAL ANGOLA CONGO NIGERIA BENIN DTVOIRE SIERRA SENEGAL GHANA THE GUINEA LIBERIA CAMEROON SOUTH AFRICA MALAWI ZAMBIA MOZAMBIQUE MADAGASCAR ZIMBABWE BOTSWANA SWAZILAND LESOTHO NAMIBIA ANGOLA WESTERN UGANDA OF THE CONGO REPUBLIC BURUNDI GUINEA REP. OF TOGO COTE BURKINA GUINEA LEONE GAMBIA BISSAU Walvis Bay SOUTH REPUBLIC AFRICAN THE AFRICA Top 15 (Swaziland, Morocco, 0.23) Bottom 15 (Niger, Eritrea, 0.002) CAPE VERDE SAO TOME & PRINCIPE SEYCHELLES MAURITIUS Highest Utilisation score: Republic of Korea, 0.64 and Utilisation… Source: ITU World Information Society Report.
BUILDING THE INFORMATION SOCIETY 2 June Disparities in Opportunity, Infrastructure, and Utilisation across Africa
BUILDING THE INFORMATION SOCIETY 2 June DOI and Income in Africa As with other regions, DOI scores for African countries illustrate the relation between per capita income and telecom development
BUILDING THE INFORMATION SOCIETY 2 June Mobile and Fixed Tracks: Africa
BUILDING THE INFORMATION SOCIETY 2 June Mobile penetration and affordability in Africa
BUILDING THE INFORMATION SOCIETY 2 June Internet use and affordability in Africa
BUILDING THE INFORMATION SOCIETY 2 June Tracking national gaps: The example of Brazil Urban/rural disparities Higher scores for states with large urban areas and/or greater administrative and economic importance for the country
BUILDING THE INFORMATION SOCIETY 2 June Brazil’s regional DOI scores
BUILDING THE INFORMATION SOCIETY 2 June A look at a gender-focused DOI: The Czech Republic Source: ITU/KADO project, UNDP, and the Czech Statistical Office
BUILDING THE INFORMATION SOCIETY 2 June Disaggregating by gender Affordability differences and cultural factors impact women’s levels of opportunity and utilisation Czech Republic
BUILDING THE INFORMATION SOCIETY 2 June Policy Options Note: Items in blue refer to policy instruments considered incompatible with competitive policies. Based on J. Bauer 2004.
BUILDING THE INFORMATION SOCIETY 2 June Some key challenges Better integration of ICT policies and national development plans Designing sustainable policies that respond to a rapidly changing and complex telecom environment Improving the national data collection process Cooperation and coordination between ICT Ministries, regulators, NSOs, industry, and other stakeholders to match policy priorities and info needs Collection of disaggregated data for classificatory variables of interest
BUILDING THE INFORMATION SOCIETY 2 June Thank you Lilia Perez-Chavolla Thank you