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Digital Transformation: Exploring big data Governance in Public Administration

Author

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  • Alexander Yukhno

    (Institute of Public Administration and Civil Service of the Russian Presidential Academy of National Economy and Public Administration)

Abstract

As economies become increasingly data-driven, big data technologies and software products are turning into key tools for managing technological processes in real time for more efficient delivery of public services to citizens. The change in the interaction between the state and society implies the creation of a unified state digital ecosystem, centered around big data. Such paradigm calls for rethinking of public administration principles ensuring the transition from an electronic state to a digital one. As a result, the likelihood of creating values ​​that meet the shifting expectations of citizens in relation to public services increases.

Suggested Citation

  • Alexander Yukhno, 2024. "Digital Transformation: Exploring big data Governance in Public Administration," Public Organization Review, Springer, vol. 24(1), pages 335-349, March.
  • Handle: RePEc:kap:porgrv:v:24:y:2024:i:1:d:10.1007_s11115-022-00694-x
    DOI: 10.1007/s11115-022-00694-x
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    References listed on IDEAS

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    1. Constantiou, Ioanna D & Kallinikos, Jannis, 2015. "New games, new rules: big data and the changing context of strategy," LSE Research Online Documents on Economics 63017, London School of Economics and Political Science, LSE Library.
    2. Clifford Lynch, 2008. "How do your data grow?," Nature, Nature, vol. 455(7209), pages 28-29, September.
    3. World Bank, 2021. "World Development Report 2021 [Informe sobre el desarrollo mundial 2021]," World Bank Publications - Books, The World Bank Group, number 35218.
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