First Monday

Geography matters: Mapping human development and digital access by Stephanie A. Birdsall and William F. Birdsall

Policy circles have long made the assumption that information and communications technologies promote human development. In mapping the Human Development Index (HDI) against the Digital Access Index (DAI) we explore the statistical and spatial relationship between human development and digital access. The results suggest information and communications technologies may not play as strong a role in promoting human development as is usually asserted and that public policies might need to be centered more on human rather than digital capital.


Human development and information and communications technologies (ICTs)
Exploring human development and digital access
Human Development Index (HDI)
Digital Access Index (DAI)
HDI and DAI statistical relationship
Mapping human development
Mapping digital access
Mapping human development and digital access
Mapping the direction of the human development and digital access relationship
Strength of spatial correlation




Information and communication technologies (ICTs) have been credited with making major contributions to human development on a global scale. Many see ICTs as both a steam engine driving the transformation to an information age in industrialized nations and as a means for developing countries to "leapfrog" various stages of their development. Others caution that at least with regard to less developed countries ICTs should not be seen as a "techno–quick–fix" for addressing development challenges. They assert that we are only just beginning to understand to what extent ICTs advance development goals and what the benefits and trade offs are in investing in their use. We concur with the view that "assembling empirical evidence on the impact of ICT on human development is of key importance" [1].

The creation of quantifiable indices of both human development and the availability and use of ICTs in national development are useful elements in assembling this empirical evidence. The recent availability of two indices allows for the further exploration of the relationship between human development and access to ICTs. The first index is the yearly Human Development Report produced by the United Nations Development Programme (UNDP) since 1990. This annual report includes a Human Development Index (HDI) that has been refined over the years. The most recent HDI, based on 2002 data for 177 nations, is contained in Human Development Report 2004 (UNDP, 2004).

The second index is the Digital Access Index (DAI) compiled by the International Telecommunications Union (ITU), an agency of the United Nations. In preparation for the United Nations World Summit on the Information Society (WSIS), the ITU devised a Digital Access Index (DAI) based on 2002 data for 178 nations (ITU, 2003).

This paper examines the statistical relationship between human development and digital access. We are interested in furthering the discussion of the spatial dimensions of this relationship taking both human development and digital access as, in part, geographic phenomena. While the rhetoric that surrounds the Internet tends to work towards diminishing, if not demolishing, the significance of space, there are a number of voices that challenge that rhetoric and assert, as Barney Warf does that "geography still matters" [2]. In order to further explore the assumptions behind this rhetoric, we map the intersections of human development and digital access. Looking at these two phenomena spatially provokes and informs public policy discussion and research of the social, cultural, economic, and political implications for human development of information and communications technology development. We conclude by identifying public policy implications of the statistical and spatial relationships between human development and digital access.



Human development and information and communications technologies (ICTs)

The widespread attention given to the relationship between ICTs and development is vividly demonstrated in the high policy and program priority given to it by the United Nations. Since the 1990s, the United Nations Development Programme (UNDP) has provided strategic ICT policy advice and assistance to developing nations through its Information and Communications Technologies for Development (ICTD) Initiative.

As well, in 2000, the United Nations adopted a set of eight Millennium Development Goals (MDG) embodying specific targets and indicators. Goal 8, "Develop a global partnership for development," includes Target 18: "In co–operation with the private sector, make available the benefits of new technologies, especially information and communications" [3]. More recently, the importance of ICTs to human development permeates the Declaration of Principles and Plan of Action formulated by the U.N. World Summit on the Information Society [4].

The importance of ICTs to national and human development is a recurring theme in the annual UNDP Human Development Reports (HDR). The 1999 HDR report, Globalization With a Human Face, includes an entire chapter on "New Technologies and the Global Race for Knowledge" (UNDP, 1999). New information and communications technologies are identified as the drivers of globalization in the Human Development Report 2000 devoted to human rights and human development [5]. The entire 2001 report, entitled Making New Technologies Work for Human Development, expresses concern about the "huge inequalities between countries — not just in terms of innovation and access, but also in the education and skills required to use technology effectively" [6]. It demonstrates the inequality through a global map of 72 nations according to their ranking on a Technology Achievement Index (TAI) [7].

The 2002 Human Development Report on Deepening Democracy in a Fragmented World emphasizes the importance of access to the Internet and independent media in strengthening the role of democracy in human development [8]. Focusing on human poverty, the 2003 report links technology and human development as a means of providing access to global knowledge [9]. Finally, the 2004 report on cultural liberty notes the importance of the ease of global communication as a challenge to cultural diversity and identity [10].

In addition to the consistent endorsement of the importance of ICTs to human development in the global Human Development Report, an UNDP regional report on nine Asian countries, Promoting ICT for Human Development in Asia 2004: Realising the Millennium Development Goals, provides an extended narrative of how ICTs contribute to human development. This narrative covers such topics as:

In addition to the UNDP global and regional reports, priority is given to ICTs reiterated in national development reports. For example, the Lithuanian Human Development Report 2002–2003 [11] is devoted to Knowledge, information, technology and human development and focuses on "human development in an information society" [12].

Thus, while debate continues over the relationship between ICTs and human and national development, the extensive array of benefits ascribed to ICTs by these global, regional, and national reports illustrates that ICTs are accepted by many at national and international levels of policy making as central to all facets of development — including globalization, human development, human rights and democracy, poverty and economic development, and culture. As a result "There is a great rush to be part of the network age — the combined result of the technological revolutions and globalization that are integrating markets and linking people across all kinds of traditional boundaries" [13]. But to what extent is there a relationship between human development and access to ICT? And if there is a relationship, can we make a contribution toward understanding it through a spatial illustration of its scope?



Exploring human development and digital access

There have been various attempts to formulate quantifiable indices to rank ICT infrastructure and its use by countries including efforts within the UNDP. As we noted earlier, Human Development Report 2001 included a Technology Achievement Index (TAI) to demonstrate inequalities in ICTs diffusion among 72 countries. Four dimensions — technology creation, diffusion of recent innovations, diffusion of old innovation, and human skills — were measured through eight indicators. Countries were given individual ranks and grouped into four categories: Leaders, Potential Leaders, Dynamic Adopters, and Marginalized. The spatial distribution of countries in these four categories was illustrated in a global map [14]. The Report claims "... the TAI shows a high correlation with the human development index (HDI), and it correlates better with the HDI than with income" [15].

Rondal Hill and Kanwalroop Dhanda (2003) use the TAI "to examine the relationship between technological achievement and human development so that the human rights community may better understand the impact of the digital divide worldwide" [16]. They found that "for the entire set of countries HDI and TAI are strongly correlated (.897), supporting the contention that the creation, dissemination, and utilization of technology and human achievement exist within an essential and potentially reciprocal relationship ..." [17]. They arrived at the not uncommon conclusion that the reciprocal relationship is one such that human development provides a necessary foundation of technology development and that "technological advances build human capabilities through the something dissemination of progress ..." [18].

Another exercise in devising ICTs indicators in relation to human development is contained in the UNDP regional report noted earlier, Promoting ICT for Human Development in Asia 2004 [19]. Indicators were devised to measure the linkages between the use of ICTs and their contribution towards achieving the UN Millennium Development Goals in nine Asian countries. After reviewing earlier efforts at devising indicators, weightings, and composite indices, the study team created an index and ranking based on 22 indicators used to capture five dimensions of ICTs development [20]. The index was not used to detect a correlation between development and ICTs but, rather, to measure the extent of the use of ICTs to achieve specific policy goals. The indicators did reveal "... enormous variations across countries in ICT availability and use of higher and lower end technologies, infrastructure, connectivity, cost, human skills, availability of locally relevant content, and types of ICT applications for human development" [21].

Gili Drori and Yong Suk Jang (2003) use several economic, political, cultural, and IT indicators, including a Net Sophistication Score, to examine factors leading to changes in IT connectivity between 1980 and 1995. They make the observation that "cross–national differences in IT resources and capabilities are sharpening global inequalities and, moreover, setting a new geography of global centrality/marginality" [22].

Based on these studies there is evidence of a relationship between the use of ICTs and human development, although the precise nature of that relationship is still a matter of debate. Whatever indicators are applied, there remains strong evidence that a global digital divide still prevails and that it has a geographic or spatial component. It is the nature of this "new geography of global centrality/marginality" that we explore in this paper.

We chose the HDI and the DAI because they are indices that:



Human Development Index (HDI)

The UNDP defines human development as "... a process of enlarging people’s choices." Three choices are identified as essential to all levels of development: "for people to lead a long and healthy life, to acquire knowledge and to have access to resources needed for a decent standard of living" [23]. Because of the complexity of human development the UNDP does not claim that the HDI is a comprehensive measure of human development. Indeed, in addition to the HDI it also undertakes separate indices measuring human poverty and gender–related development and compiles about 30 additional statistical tables on a wide range of economic, social, environmental and other issues. The HDI is published every year and, therefore, provides an opportunity to track trends over time.

The HDI uses three essential, measurable dimensions of human development through four indicators to create an index for each dimension which are then combined to generate the HDI as illustrated in Table 1.


Table 1: Human Development Index components.
Source: UNDP, 2004, p. 258.
Dimension Indicator Dimension Index
A long and healthy life Life expectancy at birth Life expectancy index
Knowledge Adult literacy rate
Gross enrollment ratio
(primary, secondary, tertiary)
Education index
A decent standard of living GDP per capita GDP index


The major sources of the HDI data are the U.N. Population Division, UNESCO Institute for Statistics, World Bank, and University of Pennsylvania Penn World Tables.

The HDI, based on 2002 data, includes 177 U.N. member countries. Sixteen U.N. members are not included due to a lack of comparable data [24]. The UNDP table provides the values for all the indicators as well as the HDI for the countries included in the table. We provide the full list of HDI values in Appendix I.



Digital Access Index (DAI)

Since the early 1990s, the International Telecommunications Union (ITU), an agency of the United Nations, has issued a series entitled World Telecommunication Development Report. The 2003 report, World Telecommunication Development Report: Access Indicators for the Information Society, was prepared for the first meeting of the World Summit on the Information Society (WSIS) in Geneva, 10–12 December 2003. The Development Report is devoted to measuring access to ICTs including the development and compiling of the Digital Access Index. This initiative was undertaken based on the premise "that access to ICTs is doubtless the most fundamental prerequisite for an inclusive information society" [25].

The Report acknowledges that technical infrastructure is a key component in the provision of access but it has too often been the only factor measured. New indicators were considered necessary to capture the importance of such factors as affordability and knowledge. Other ICT indices were rejected by the ITU because they included a limited number of countries, were not designed to measure access specifically, were methodologically flawed, or were not transparent due to the use of a larger number of variables. The intent of the DAI is to measure "the overall ability of individuals in a country to access and use new ICTs" based on five factors: infrastructure, affordability, knowledge, quality, and actual usage. Eight indicators were used to measure these five factors as shown in Table 2. The maximum value for each indicator is derived by dividing the indicator by a "goalpost" [26].


Table 2: Digital Access Index components.
Source: ITU, 2003, Table 5.1, p. 21.
Factor Indicator Goalpost
Infrastructure Fixed telephone subscribers per 100 inhabitants
Mobile subscribers per 100 inhabitants
Knowledge Adult literacy
Overall school enrollment
Affordability Internet access price (20 hours per month) as percent of per capita income 100
Quality Broadband subscribers per 100 inhabitants
International Internet bandwidth per capita
Internet usage Internet users per 100 inhabitants 85


The DAI includes 178 countries. Countries are classified as having high, upper, medium, or low ICT access. We provide the DAI values in Appendix II. Like the 2004 HDI, the DAI is based on 2002 data. It is not yet determined if the DAI will be issued on a regular basis. The ITU is recommending that agreement on a core set of information society access indicators be a goal for the second phase meeting of the WSIS in Tunis in 2005. DAI values are listed in Appendix II.



HDI and DAI statistical relationship

As outlined earlier, numerous studies have established a relationship between human development and digital access indicators. That statistical relationship is also apparent between the indices we are studying, the Human Development Index and the Digital Access Index. Pearson’s correlation coefficient, which expresses the linear relationship between two continuous variables, can be used to measure that relationship. We used SPSS to produce the following correlation table. Note that the correlation coefficient between the two variables is .902 and that the results are significant at 0.01 level.


HDI Pearson correlation 1 .902*
Sig. (2–tailed)   .000
N 177 177
DAI Pearson correlation .902* 1
Sig. (2–tailed) .000  
N 177 177
* Correlation is significant at the 0.01 level (2–tailed).


These results indicate that there is a statistically significant relationship between these indices and that relationship is one of strong, positive correlation. Part of this relationship may be explained by the fact that the two indices share at least one variable: adult literacy. Nonetheless, our result supports the findings of others that there is a strong relationship between human development and digital access.

However, we need to keep in mind that correlation is not causation; this correlation gives little direction in terms of policy. To explore further this relationship, we turn now to our spatial analysis of the relationship.



Mapping human development

Before exploring the spatial relationship between human development and digital access we first map the values of the HDI in Figure I and the DAI in Figure 2.


HDI values

Figure 1: Human Development Index values.


The countries that are represented in the HDI (that are given values) are divided into four categories: low development, middle development, upper development and high development. The lower values are represented by the lighter blues, the higher values by the darker blues. Countries that are white, for example Zaire, are ones that are not represented in the HDI. In examining Figure I, there appear to be regional clusters of countries reflecting the four categories of human development; thus, there does seem to be a geographic or spatial dimension to human development.



Mapping digital access

A map of the DAI (Figure 2) yields a similar conclusion. Again there appear to be regional clusters of DAI values representing a spatial dimension to digital access.


DAI values

Figure 2: Digital Access Index values.


As with the HDI map, countries that are represented in the DAI (that are given values) are divided into four categories: low digital access, middle digital access, upper digital access and high digital access. Vertical and horizontal lines represent the low and middle categories and diagonal lines indicate the upper and high categories.



Mapping human development and digital access

In order to see if there is a spatial representation of the statistical relationship we reported above, we combine the two maps in Figure 3. The similarities of the spatial locations of the values show clearly when the two maps are combined.


DAI vs HDI values

Figure 3: Digital Access Index values mapped against Human Development Index values.


In Figure 3, we clearly see the statistical correlation spatially expressed. In particular, we find in North America, Western Europe, Japan, and Australia countries high in both human development and digital access. This clustering and relationship is not unexpected. Of more interest are those countries where there is a difference between their HDI and DAI.



Mapping the direction of the human development and digital access relationship

Using ArcGIS we can do a further analysis of the relationship between the Digital Access Index and the Human Development Index. The literature on development and ICTs implies that ICTs foster development, if they are not indeed a prerequisite. To examine that alleged relationship, in Figure 4 we explore the degree to which countries fall into the same category in both indices. Recall that both indices rank countries as either low, middle, upper, or high.

Figure 4 is a map of the countries that have upper or high scores on the Human Development Index with middle or low scores on the Digital Access Index. These 37 countries, outlined in yellow on the map, are Azerbaijan, Albania, Armenia, Belize, Bosnia and Herzegovina, Sri Lanka, Colombia, Cuba, Cape Verde, Dominican Republic, Ecuador, El Salvador, Fiji, Georgia, Guyana, Iran, Jordan, Kazakhstan, Lebanon, Libya, Oman, Maldives, Suriname, Paraguay, Peru, Panama, Romania, Philippines, Saudi Arabia, Thailand, Tonga, Tunisia, Turkey, Turkmenistan, Ukraine, Uzbekistan, and Venezuela.



Figure 4: Countries with upper or high values on the Human Development Index and middle or low values on the Digital Access Index.


There are no countries that fit the opposite pattern, that is, with low to middle scores in Human Development Index and upper to high scores on the Digital Access Index. Only Swaziland’s HDI score is in the low category while its DAI score is in the middle category. In all other cases, a country’s DAI score falls into the same or into a lower category than its HDI. This result brings into question the nature of the correlation relationship. That countries are either in the same ranking category for human development and digital access or in a higher human development ranking than their digital access ranking is suggestive of HDI as a prerequisite to digital development rather than the converse. The maps seem to indicate that this "new geography" is not so new after all. As Warf argues "Access to the Internet is deeply conditioned by where one is, which is in turn a reflection of relations of wealth and power" [27].

Similarly, Stephanie Birdsall (2005), in her study on the potential impact of internet access on voting patterns, maintains

"while the rhetoric of the internet is one of both decentralization and connectedness, the behavior of Internet activity is similar to other social phenomena. It tends to cluster around centers of cultural and economic power and instead of creating new connections, it reinforces other indicators of connectedness, including potentially voting."

Gili S. Dori and Yong Suk Jang (2003) conclude that non–economic factors account for changes in IT connectivity over time. In particular, education and science play a central role in a country’s move to greater IT connectivity. It is arguable that education and science are driven more by human, rather than digital, capital.



Strength of spatial correlation

Here we explore further the relationship between human development and digital access using ArcView to calculate more precisely whether the visual impression of clustering is borne out statistically (as an autocorrelation). Moran’s I statistic is most often used to measure the spatial autocorrelation of variables; that is, to determine the strength of the correlation between the value of a variable and its location in space. If a variable’s value has a positive correlation to values of locations nearby, the Moran’s I will be >0 (approaching 1 according to the strength of the correlation). If a variable’s value has a negative correlation with neighboring values, the Moran’s I will be <0 (approaching -1). If there is no correlation, that is, if the values are distributed in space randomly, then the Moran’s I will be 0. Not surprisingly, considering the strength of their correlation as measured by Pearson’s coefficient, both HDI and DAI have similar Moran’s I values. HDI has a Moran’s I of 0.28 and DAI has a Moran’s I of 0.27.

Additionally, referring back to Figures 1 and 2, it appears there is a clustering of low values for both DAI and HDI in sub–Sahara Africa and a clustering of high values in Europe. Figure 4, which maps the countries that have HDI scores that fall into the upper two categories and DAI scores that fall into the lower two categories, displays clusterings as well. In addition to illustrating Tobler’s first law of geography that, "all things are related, but nearby things are more related than distant things," this clustering lends further weight to the idea that both the HDI and DAI have a strong spatial component.

The apparent strong relationship between spatial location and human and digital development raises questions that warrant further exploration. What is the degree to which spatial location matters more than policy? What policy can help a country overcome the limits of its spatial location? What is it about human development and digital access that both phenomena are so sensitive to location?




Using the Human Development Index and the Digital Access Index we have explored the statistical and spatial relationship between human development and digital access. We found a strong statistical correlation between the HDI and DAI, a result that supports others who have examined the statistical relationship between development and information and communication technologies. We provide a separate mapping of the HDI and of the DAI (Figures 1 and 2 respectively). As well, we combined the two (Figure 3) to provide a visual spatial representation of the relationship.

We further explored the spatial relationship by identifying in Figure 4 countries that are stronger in human development than in digital access. We found 37 countries whose HDI was in the upper or high categories but DAI was in the middle or low categories. In contrast, we found only one country that was stronger in digital access than human development (Swaziland). This result suggests that digital access may not play as strong a role in promoting human development as is usually asserted. This further suggests to us that public policies might need to be centered more on human rather than digital capital. There is a need for further research to examine the proposition that human development leads to ICT development rather than the converse.

Our analysis found that with both indices countries appear to fall into regional clusters. We confirmed that there is a statistical relationship (autocorrelation) within the regional clusters signifying that geography or location does, indeed, matter. This clustering suggests to us that cultural (including economic and political) factors within a region may be more significant with regard to advancing human development than technological ones. Technological advances might more accurately be seen as resulting from, rather than, driving advances in human development. From a public policy perspective, we propose that public policy development strategies that give a high priority to human development in a regional cultural context could be more productive than either broad international or local national strategies that give high priority to ICT development. End of article


About the authors

Stephanie A. Birdsall is the Communications Specialist for Computing and Information Services at Brown University.
Direct comments to stephanie_birdsall [at] brown [dot] edu

William F. Birdall is a library consultant.
E–mail: billbirdsall [at] accesswave [dot] ca



1. UNDP 2004 reg report, p. 29.

2. Warf, 2001, p. 3.

3. United Nations, Statistical Division, 2005. "Millennium Development Goal Indicators Database," at, accessed 23 September 2005.

4. See;

5. UNDP, 2000, p. 6.

6. UNDP, 2001, p. 3.

7. UNDP, 2001, p. 45.

8. UNDP, 2002, p. 77.

9. UNDP, 2003, pp. 157–160.

10. UNDP, 2004, p. 2.


12. UNDP in Lithuania, 2003, p. 7.

13. UNDP, 2001, p. 1.

14. UNDP, 2001, p. 45.

15. UNDP, 2001, p. 47.

16. Hill and Dhanda, 2003, p. 1020.

17. Hill and Dhanda, 2003, p. 1028.

18. Hill and Dhanda, 2003, p. 1029.


20. UNDP, APDIP, 2005, pp. 29–38.

21. UNDP, APDIP, 2005, p. 53.

22. Drori and Jang, 2003, p. 156.

23. UNDP, 1990, p. 10.

24. Fuller information on the HDI statistics and methodology can be found in Human Development Report 2004, pp. 127–138. The HDI table from which we have extracted our data is on pp. 139–142 of HDR 2004.

25. Their emphasis; ITU, 2003, p. 4.

26. The complete formula can be found at ITU, 2003, Table 5.1, 21.

27. Warf, 2000, p. 19.



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Appendix I: Human Development Index ranking.
Source: UNDP at
High HDI Upper HDI Middle HDI Low HDI
Norway 0.956 Costa Rica 0.834 Algeria 0.704 Bhutan 0.536
Sweden 0.946 Uruguay 0.833 Equatorial Guinea 0.703 Lao People’s Dem. Rep. 0.534
Australia 0.946 Qatar 0.833 Kyrgyzstan 0.701 Comoros 0.530
Canada 0.943 Croatia 0.830 Indonesia 0.692 Swaziland 0.519
Netherlands 0.942 United Arab Emirates 0.824 Viet Nam 0.691 Bangladesh 0.509
Belgium 0.942 Latvia 0.823 Moldova, Rep. of 0.681 Sudan 0.505
Iceland 0.941 Bahamas 0.815 Bolivia 0.681 Nepal 0.504
United States 0.939 Cuba 0.809 Honduras 0.672 Cameroon 0.501
Japan 0.938 Mexico 0.802 Tajikistan 0.671 Pakistan 0.497
Ireland 0.936 Trinidad and Tobago 0.801 Mongolia 0.668 Togo 0.495
Switzerland 0.936 Antigua and Barbuda 0.800 Nicaragua 0.667 Congo 0.494
United Kingdom 0.936 Bulgaria 0.796 South Africa 0.666 Lesotho 0.493
Finland 0.935 Russian Federation 0.795 Egypt 0.653 Uganda 0.493
Austria 0.93 Libyan Arab Jamahiriya 0.794 Guatemala 0.649 Zimbabwe 0.491
Luxembourg 0.933 Malaysia 0.793 Gabon 0.648 Kenya 0.488
France 0.932 Macedonia, TFYR 0.793 São Tomé and Principe 0.645 Yemen 0.482
Denmark 0.932 Panama 0.79 Solomon Islands 0.624 Madagascar 0.469
New Zealand 0.926 Belarus 0.790 Morocco 0.620 Nigeria 0.466
Germany 0.925 Tonga 0.787 Namibia 0.607 Mauritania 0.465
Spain 0.922 Mauritius 0.785 India 0.595 Haiti 0.463
Italy 0.920 Albania 0.781 Botswana 0.589 Djibouti 0.454
Israel 0.908 Bosnia and Herzegovina 0.781 Vanuatu 0.570 Gambia 0.452
Hong Kong, China (SAR) 0.903 Suriname 0.780 Cambodia 0.568 Eritrea 0.439
Greece 0.902 Venezuela 0.778 Ghana 0.568 Senegal 0.437
Singapore 0.902 Romania 0.778 Myanmar 0.551 Timor–Leste 0.436
Portugal 0.897 Ukraine 0.777 Papua New Guinea 0.542 Rwanda 0.431
Slovenia 0.895 Saint Lucia 0.777   Guinea 0.425
Korea, Rep. of 0.888 Brazil 0.775   Benin 0.421
Barbados 0.888 Colombia 0.773   Tanzania, U. Rep. of 0.407
Cyprus 0.883 Oman 0.770   Côte d’Ivoire 0.399
Malta 0.875 Samoa (Western) 0.769   Zambia 0.389
Czech Republic 0.868 Thailand 0.768   Malawi 0.388
Brunei Darussalam 0.867 Saudi Arabia 0.768   Angola 0.38
Argentina 0.853 Kazakhstan 0.766   Chad 0.379
Seychelles 0.853 Jamaica 0.764   Congo, Dem. Rep. of the 0.365
Estonia 0.853 Lebanon 0.758   Central African Republic 0.361
Poland 0.850 Fiji 0.758   Ethiopia 0.359
Hungary 0.848 Armenia 0.754   Mozambique 0.354
Saint Kitts and Nevis 0.844 Philippines 0.753   Guinea–Bissau 0.350
Bahrain 0.843 Maldives 0.752   Burundi 0.339
Lithuania 0.842 Peru 0.752   Mali 0.326
Slovakia 0.842 Turkmenistan 0.752   Burkina Faso 0.302
Chile 0.839 Saint Vincent and the Grenadines 0.751   Niger 0.292
Kuwait 0.838 Turkey 0.751   Sierra Leone 0.273
  Paraguay 0.751    
  Jordan 0.750    
  Azerbaijan 0.746    
  Tunisia 0.745    
  Grenada 0.745    
  China 0.745    
  Dominica 0.743    
  Sri Lanka 0.740    
  Georgia 0.739    
  Dominican Republic 0.738    
  Belize 0.737    
  Ecuador 0.735    
  Iran, Islamic Rep. of 0.732    
  Occupied Palestinian Territories 0.726    
  El Salvador 0.720    
  Guyana 0.719    
  Cape Verde 0.717    
  Syrian Arab Republic 0.710    
  Uzbekistan 0.709    



Appendix II: Digital Access Index rankings (2002 data).
Source: ITU, 2003, Table 5.2, p. 22.
High access Upper access Middle access Low access
Sweden 0.85 Ireland 0.69 Belarus 0.49 Zimbabwe 0.29
Denmark 0.83 Cyprus 0.68 Lebanon 0.48 Honduras 0.29
Iceland 0.82 Estonia 0.67 Thailand 0.48 Syria 0.28
Korea (Rep.) 0.82 Spain 0.67 Romania 0.48 Papua New Guinea 0.26
Norway 0.79 Malta 0.67 Turkey 0.48 Vanuatu 0.24
Netherlands 0.79 Czech Republic 0.66 TFYR Macedonia 0.48 Pakistan 0.24
Hong Kong, China 0.79 Greece 0.66 Panama 0.47 Azerbaijan 0.24
Finland 0.79 Portugal 0.65 Venezuela 0.47 São Tomé and Principe 0.23
Taiwan, China 0.79 United Arab Emirates 0.64 Belize 0.47 Tajikistan 0.21
Canada 0.78 Hungary 0.63 St. Vincent 0.46 Equatorial Guinea 0.20
United States 0.78 Bahamas 0.62 Bosnia 0.46 Kenya 0.19
United Kingdom 0.77 St. Kitts and Nevis 0.60 Suriname 0.46 Nicaragua 0.19
Switzerland 0.76 Poland 0.59 South Africa 0.45 Lesotho 0.19
Singapore 0.75 Slovak Republic 0.59 Colombia 0.45 Nepal 0.19
Japan 0.75 Croatia 0.59 Jordan 0.45 Bangladesh 0.18
Luxembourg 0.75 Bahrain 0.58 Serbia and Montenegro 0.45 Yemen 0.18
Austria 0.75 Chile 0.58 Saudi Arabia 0.44 Togo 0.18
Germany 0.74 Antigua and Barbuda 0.57 Peru 0.44 Solomon Islands 0.17
Australia 0.74 Barbados 0.57 China 0.43 Uganda 0.17
Belgium 0.74 Malaysia 0.57 Fiji 0.43 Zambia 0.17
New Zealand 0.72 Lithuania 0.56 Botswana 0.43 Myanmar 0.17
Italy 0.72 Qatar 0.55 Iran (I.R.) 0.43 Congo 0.17
France 0.72 Brunei Darussalam 0.55 Ukraine 0.43 Cameroon 0.16
Slovenia 0.72 Latvia 0.54 Guyana 0.43 Cambodia 0.16
Israel 0.70 Uruguay 0.54 Philippines 0.43 Lao P.D.R. 0.15
  Seychelles 0.54 Oman 0.43 Ghana 0.15
  Dominica 0.54 Maldives 0.43 Malawi 0.15
  Argentina 0.53 Libya 0.42 Tanzania 0.15
  Trinidad and Tobago 0.53 Dominican Rep. 0.42 Haiti 0.15
  Bulgaria 0.53 Tunisia 0.41 Nigeria 0.15
  Jamaica 0.53 Ecuador 0.41 Djibouti 0.15
  Costa Rica 0.52 Kazakhstan 0.41 Rwanda 0.15
  St. Lucia 0.52 Egypt 0.40 Madagascar 0.15
  Kuwait 0.51 Cape Verde 0.39 Mauritania 0.14
  Grenada 0.51 Albania 0.39 Senegal 0.14
  Mauritius 0.50 Paraguay 0.39 Gambia 0.13
  Russia 0.50 Namibia 0.39 Bhutan 0.13
  Mexico 0.50 Guatemala 0.38 Sudan 0.13
  Brazil 0.50 El Salvador 0.38 Comoros 0.13
    Palestine 0.38 Côte d’Ivoire 0.13
    Sri Lanka 0.38 Eritrea 0.13
    Bolivia 0.38 D.R. Congo 0.12
    Cuba 0.38 Benin 0.12
    Samoa 0.37 Mozambique 0.12
    Algeria 0.37 Angola 0.11
    Turkmenistan 0.37 Burundi 0.10
    Georgia 0.37 Guinea 0.10
    Swaziland 0.37 Sierra Leone 0.10
    Moldova 0.37 Central African Rep. 0.10
    Mongolia 0.35 Ethiopia 0.10
    Indonesia 0.34 Guinea–Bissau 0.10
    Gabon 0.34 Chad 0.10
    Morocco 0.33 Mali 0.09
    India 0.32 Burkina Faso 0.08
    Kyrgyzstan 0.32 Niger 0.04
    Uzbekistan 0.31  
    Viet Nam 0.31  
    Armenia 0.30  



Editorial history

Paper received 7 September 2005; accepted 20 September 2005.

Creative Commons License
This work is licensed under a Creative Commons Attribution–NonCommercial–NoDerivs 2.5 License.

Geography matters: Mapping human development and digital access
by Stephanie A. Birdsall and William F. Birdsall
First Monday, Volume 10, Number 10 - 3 October 2005