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What is Progressor Cluster

Handbook of Research on Applied Data Science and Artificial Intelligence in Business and Industry
This group is one step higher than the Emergent and includes those nations that are progressing and expanding their e-government services.
Published in Chapter:
Examining the Evolution of E-Government Development of Nations Through Machine Learning Techniques
Niguissie Mengesha (Brock University, Canada) and Anteneh Ayanso (Brock University, Canada)
DOI: 10.4018/978-1-7998-6985-6.ch004
Abstract
Several initiatives have tried to measure the efforts nations have made towards developing e-government. The UN E-Government Development Index (EGDI) is the only global report that ranks and classifies the UN Member States into four categories based on a weighted average of normalized scores on online service, telecom infrastructure, and human capital. The authors argue that the EGDI fails in showing the efforts of nations over time and in informing nations and policymakers as to what and from whom to draw policy lessons. Using the UN EGDI data from 2008 to 2020, they profile the UN Member States and show the relevance of machine learning techniques in addressing these issues. They examine 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, they discuss the policy implications of the proposed methodology and the insights obtained.
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