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How World-Wide is the Web and How Much of a Web is it Anyway?. Han Reichgelt. Agenda. IT and Economic Development Obstacles to e-commerce in developing countries The Digital Divide Active web participation (AWP) versus passive web participation (PWP) Measuring national differences in PWP

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  • IT and Economic Development
  • Obstacles to e-commerce in developing countries
  • The Digital Divide
  • Active web participation (AWP) versus passive web participation (PWP)
  • Measuring national differences in PWP
  • The Digital Divide reconsidered
  • Some conclusions and further research.
it and economic development
IT and economic development
  • Many authors and international organizations argue that IT provides an excellent opportunity for developing countries to
    • “Improve their internal operations”.
    • Strengthen and diversify their economies
it and governmental improvement
IT and governmental improvement
  • Talero and Gaudette (Worldbank)
  • IT can lead to
    • Greater governmental efficiency.
      • E.g. payment of statutory deductions via the Web in Jamaica.
    • Greater transparency and hence less opportunity for corruption.
      • E.g. an automated land information system in Karnataka in India.
    • Reduced environmental pressures
      • E.g. a web-based waste exchange in Jamaica.
    • Greater educational attainment.
strengthen and diversify economies
Strengthen and diversify economies
  • Use IT to help small and medium sized enterprises
    • E.g. use of Internet to help small farmers in Western Jamaica.
  • Provision of IT services for export
    • India, China
    • Not clear how well this strategy would work for small developing countries.
  • Possibilities of e-commerce
    • To market goods and services
      • Wapisiana hammock weavers in Rupununi inGuyana (
    • To attract direct foreign investment.
      • Investment portals, e.g.,
  • People factors
    • Unavailability of necessary technical skills
  • Business infrastructure
  • Regulatory environment
  • Client interface
    • E.g. trust, shared language.
  • Technological infrastructure
    • The digital divide
the digital divide
The Digital Divide
  • There is glaring discrepancy in access to IT between rich and poor countries, as measured in
    • Number of telephone lines
    • Number of Internet users
    • Number of Internet hosts
    • Number of PCs
    • And so on.
  • Internet use is therefore less prevalent in poor countries than it is in rich.
refining the notion of the digital divide
Refining the notion of the digital divide
  • Wolcott et al suggest measuring national Internet use in terms of
    • Pervasiveness (number of users)
    • Geographic dispersion
    • Sectoral absorption
    • Connectivity infrastructure
    • Organizational infrastructure.
    • Sophistication of use.
  • Norris, Servon, Warschauer refine the notion of a digital divide in terms of:
    • Access to relevant content and language
    • Literacy and access to education
    • Absence of supporting social structures.
active web participation versus passive web participation
Active Web Participation versus Passive Web Participation
  • The digital divide is defined primarily in terms of access. However, for economic development, access is less important than being accessed.
  • We therefore distinguish between
    • Active Web Participation
      • Making information available on the Web, and using the Web to find information.
    • Passive Web Participation
      • Attracting traffic to one’s web sites.
  • Question:
    • Is there as prevalent a digital divide in Passive Web Participation as there is in Active Web Participation?
measuring national differences in pwp country selection
Measuring national differences in PWP: Country selection
  • In our country selection, we needed to control for
    • Income
    • Population size
      • To attempt to get a measure of PWP per capita.
  • 3 categories for income
    • High: > $20,000 per capita
    • Medium: >$3,200 and < $6,500
    • Low: < $1,900
  • 3 categories for size
    • Large: >59 million
    • Medium: >17.9 million and <30.5 million
    • Small: < 6.1 million
finding different web sites
Finding different web sites
  • Located sites in each country by typing the name of the country (in English and in the national language) in google.
  • From first 50 sites found, we eliminated:
    • Personal web pages
    • Different web pages in the same top-level domain
    • Web pages created and managed somewhere else
      • Look at URL
      • Look for contact information
  • Found 50 sites for all, except Algeria (44), Sudan (43), Ethiopia (34), Benin (15) and CAR (14).
measuring national pwp
Measuring national PWP
  • Used Alexa to gather statistics for traffic to each site (
  • Alexa rank orders web sites based on “reach” (number of users) and “pageviews” (number of pages requested by a user).
  • Based on traffic ranks, we selected 10 most frequently visited sites for each country (except for Benin (9) and CAR (7)).
  • We then calculated average traffic ranks for each country on 4 different occasions and we rank-ordered countries.
measuring awp
Measuring AWP
  • We measured AWP based on
    • Internet users per 10,000 population
    • Internet hosts per 10,000 population
    • PC per 1,000 population
conclusions and shortcomings
Conclusions and Shortcomings
  • The digital divide seems to be as wide for PWP as it is for AWP.
  • But
    • Limitations in the Alexa tool bar
      • Works only under Explorer
      • Geographical differences in adoption of Alexa tool bar.
    • Our sampling method ignored the intent of the web sites.
    • Where did the visitors come from? Were they domestic or did they come from abroad?
intent of web sites in our sample
Intent of web sites in our sample
  • Around 145 web sites (75%) did not seem to have direct commercial intent
    • About 70 were newspapers.
    • About 65 were non-commercial portals and entertainment sites (television stations, etc.)
  • 45 seemed to have commercial intent
    • About 20 sites were general information sites for a country, equally distributed over our sample.
    • 12 of the remaining sites were in high-income countries, and 6 each in low and medium income countries.
    • Only 2 of the latter seemed to be directed at an international audience (tourism portals for Vietnam and Algeria).
domestic or foreign visitors
Domestic or foreign visitors?
  • Evidence for preponderance of domestic visitors:
    • High correlation between traffic rank and measures of AWP.
    • Most of the web sites in our sample were in the language of the country in which it was administered.
further research
Further research
  • Is it indeed the case that web users are primarily interested in domestic sites, or was this effect an artifact of our sampling method?
  • What drives people to visit particular web sites in the first place?
  • Despite its limitations, our results strongly suggest that low- and medium-income countries do not attract large numbers of visitors to their web sites.
  • Clearly, this is a problem for those who argue that the Internet and the Web levels the playing field for such countries.