This research first investigates the relationship between the gross national product and the amount of internet usage (per 1000 people) in the 51 sample countries from Africa. It indicates that the outlier countries in this case, i.e. countries that have an extraordinary high amount (in this case the outliers were all above the best-fit line) of internet users compared to their GDP/capita, from the sample are Seychelles, Sao Tome and Principe. After the investigation to find the outlier countries a short description of these countries is given, presenting the relevant data regarding these countries. Furthermore an investigation into the possible relevant factors affecting the number of internet users is done. These factors are found to be: country area, urbanization, trade, GDP composition by sector, education spending, literacy, and the business climate prevailing in the country.
[...] Internet usage in African countries: Empirical study on the antecedents of internet usage in developing countries Abstract This research first investigates the relationship between the gross national product and the amount of internet users (per 1000 people) in the 51 sample countries from Africa. It indicates that the outlier countries in this case, i.e. countries that have an extraordinary high amount (in this case the outliers were all above the best-fit line) of internet users compared to their GDP / capita, from the sample are Seychelles and Sao Tome and Principe. [...]
[...] We can see there that the mean and the median for the internet users are 9.83 and 3 users respectively. The standard deviation and the variance for the same variable are 19.66 and 386.70 respectively and the range of observations is 111.82 with 111.84 being the maximum observation. For the GDP / capita the mean and the median are 2298.45 and 1189.49 respectively and the standard deviation and the variance are 2373.77 and The range for the GDP / capita data is 9507.34 with 10000.3 being the maximum observation Finding outliers After the data collection we plotted the data on a scatter plot which can be found in appendix 2. [...]
[...] Table 4 in Appendix 1 lists the residuals for all the 51 countries and there we can see that two countries have a residual greater than the previously mentioned number. These countries are: Seychelles and Sao Tome and Principe. We can conclude that from this data of 51 countries there are two observations that are outliers and these are thus the countries that we will use for further analysis of the reasons behind the possible factors that cause these countries to be outliers. Chapter 3 Outlier Countries Previous chapter concluded in determining the two outlier countries that we will analyze in this research. [...]
[...] Thus we argue that a free business climate and the fact that foreign companies are investing relatively much to the country affect and promote the high per capita internet usage Factors that influence the high internet usage in Sao Tome and Principe As Seychelles, Sao Tome and Principe is a small island nation on the coast of Africa. In our sample they rank second smallest in area after Seychelles. This, as its own, is already a major factor behind the extraordinary high internet usage in the country. The same arguments which hold for Seychelles hold also here regarding the benefits of building an infrastructure for physical communication channels in a small country. [...]
[...] The GDP composition from the service industry ranks 4th in our sample indicating a high percentage of income coming from businesses like hotels, restaurants and banks. This in effect increases the need for communication channels where internet nowadays plays an important role. As in the case of Seychelles we argue that this factor is highly relevant in explaining the high internet usage in the country. Finally a rather important factor in explaining the high internet usage in Sao Tome and Principe is the foreign investments and the general business climate in the country. [...]
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