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Economic Development in the Digital Economy: A Bibliometric Review

Author

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  • Waleed Kalf Al-Zoubi

    (Department of Financial and Administrative Sciences, Amman University College, Al-Balqa Applied University, Amman 11937, Jordan)

Abstract

This study aims to investigate economic development in the digital economy and uncover trends and insights that might contribute to future research. Furthermore, the study, examining English-language publications from 2000 to 2023 in the Web of Science Core Collection, employs bibliometric and content analysis to statistically evaluate the field of economic development in the digital economy. Co-citation, co-authorship, and bibliographical coupling analyses revealed China, the Chinese Academy of Sciences (CAS), and “Sustainability” as the leading influencers in terms of country, institution, and journal, respectively. Five key themes emerged: (1) the interplay between digital technologies and economic growth, (2) leveraging digital tools for businesses, (3) the applications and impacts of diverse digital technologies across sectors, (4) the broader social implications of the digital economy, and (5) government policies for fostering digital economic progress. The study concludes by proposing avenues for further investigation.

Suggested Citation

  • Waleed Kalf Al-Zoubi, 2024. "Economic Development in the Digital Economy: A Bibliometric Review," Economies, MDPI, vol. 12(3), pages 1-30, February.
    • Handle: RePEc:gam:jecomi:v:12:y:2024:i:3:p:53-:d:1343044
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    References listed on IDEAS

    as
    1. Mingran Wu, 2023. "The impact of eco-environmental regulation on green energy efficiency in China - Based on spatial economic analysis," Energy & Environment, , vol. 34(4), pages 971-988, June.
    2. Nees Jan Eck & Ludo Waltman, 2017. "Citation-based clustering of publications using CitNetExplorer and VOSviewer," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1053-1070, May.
    3. Waltman, Ludo & van Eck, Nees Jan & Noyons, Ed C.M., 2010. "A unified approach to mapping and clustering of bibliometric networks," Journal of Informetrics, Elsevier, vol. 4(4), pages 629-635.
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