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Big data analytics and e-governance: Actors, opportunities, tensions, and applications

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  • Abuljadail, Mohammad
  • Khalil, Ashraf
  • Talwar, Shalini
  • Kaur, Puneet

Abstract

We present a systematic review of peer-reviewed articles, empirical as well as conceptual, investigating the integration of big data analytics in e-governance within business management, decision sciences, social sciences, and policy literature. Our primary objective in undertaking this review is to better understand the competing and conflicting scholarly perspectives on the integration of big data analytics in the delivery of governance, public services, and evidence-based policymaking. We focus particularly on a critical assessment of the literature to identify visible as well as less perceptible gaps in extant research to set a comprehensive future research agenda. In addition, we also aim to dig deeper into the landscape of the available research in terms of the volume of scientific production and other bibliometric characteristics to gauge the extent and nature of scholarly engagement with the area to inform future research. To these ends, we executed our systematic review through a four-step process of scoping, specification and execution of search protocols, short-listing of congruent literature, and quantitative and qualitative data analysis. In all, we identified 45 articles that attended to big data analytics and e-governance as the core concerns or themes. Our analysis generated four pillars on which the academic contributions in the area rest: actors, opportunities, tensions, and applications. We critically synthesized the findings around these four pillars to map the gaps and develop potential research questions that future researchers can address to expand the evidence and insights in the area to influence policy and governance.

Suggested Citation

  • Abuljadail, Mohammad & Khalil, Ashraf & Talwar, Shalini & Kaur, Puneet, 2023. "Big data analytics and e-governance: Actors, opportunities, tensions, and applications," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    • Handle: RePEc:eee:tefoso:v:193:y:2023:i:c:s0040162523002974
    DOI: 10.1016/j.techfore.2023.122612
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