Abstract

E-government has been one of the top government strategies in recent years. Several studies and projects have attempted to understand the scope of e-government and the measurement framework that can be deployed to track the readiness as well as progress of nations overtime. Among these initiatives is the United Nations Public Administration Network (UN PAN) that assesses the e-government readiness of nations according to a quantitative composite index based on telecommunication infrastructure, human capital, and online services. Using the UN PAN index data from 2008 to 2016, the article profiles African nations using unsupervised machine learning technique. It also examines the resulting cluster profiles in terms of theoretical perspectives in the literature and derive policy insights from the different groupings of nations and their evolution over time. Finally, the article discusses the policy implications of the proposed methodology and the insights obtained.

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