Data-driven E-Government: Exploring the Socio-Economic Ramifications




Data-Driven e-Government, Data-Driven Decision Making, Big Data, Data Analytics, Value Creation, Public Sector


The evident benefits of big data, artificial intelligence and machine learning in society have begun to influence the transition towards a data-driven public sector. Decision-making in the public sector is in an infancy phase of a revolution owing to the inclusion of these new technological innovations. Research has revealed that data-driven e-government policies improve socio-economic development in some nations. Despite the immense opportunities data-driven e-government models have for governments, similar to every system, there are ramifications. This study explores the concept of data-driven e-government as well as investigates the socio-economic implications such an e-government model can have on society. Findings of this exploratory study add insight into a field which is in its early days and still unfocused, as well as making recommendations for policymakers.


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Author Biographies

Ebenezer Agbozo, Ural Federal University

Ebenezer Agbozo is a PhD Candidate at the Ural Federal University in Yekaterinburg, Russia. He also works as a lecturer at the department of Systems Analysis and Decision Making of the Graduate School of Economics and Management. His research focuses on e-Government, Information Communication Technology for Development (ICT4D), Web Services, Big Data, Data Mining, and Social Informatics.

Benjamin Kwesi Asamoah, Ural Federal University

Benjamin Kwesi Asamoah is a masters student and junior researcher at the Ural Federal University. His research focuses on the application of statistical and econometric techniques in the area of socio-economic development in developing economies.


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How to Cite

Agbozo, E., & Asamoah, B. K. (2019). Data-driven E-Government: Exploring the Socio-Economic Ramifications. JeDEM - EJournal of EDemocracy and Open Government, 11(1), 81-90.