How World-Wide is the Web and How Much of a Web is it Anyway?

1. How World-Wide is the Web and How Much of a Web is it Anyway? Han Reichgelt

2. 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 • The Digital Divide reconsidered • Some conclusions and further research.

3. 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

4. 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.

5. 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 (www.gol.net.gy/rweavers/) • To attract direct foreign investment. • Investment portals, e.g., www.investjamaica.com

6. Obstacles • People factors • Unavailability of necessary technical skills • Business infrastructure • Regulatory environment • Client interface • E.g. trust, shared language. • Technological infrastructure • The digital divide

7. 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.

8. 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.

9. 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?

10. 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

11. Measuring national differences in PWP: Country selection

12. Location of some countries

13. 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).

14. Measuring national PWP • Used Alexa to gather statistics for traffic to each site (www.alexa.org). • 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.

16. Results: Rank-order of countries based on PWP

17. Measuring AWP • We measured AWP based on • Internet users per 10,000 population • Internet hosts per 10,000 population • PC per 1,000 population

18. Results: Rank-order of countries based on AWP (Internet users per 10,000)

19. Results: Rank-order of countries based on AWP (Internet hosts per 10,000)

20. Results: Rank-order of countries based on AWP (PCs/1000)

21. Some Spearman rank-order correlations

22. 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?

23. 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).

24. 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.

25. 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?

26. Conclusion • 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.