IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0328683.html
   My bibliography  Save this article

Determinant factors of Chief Data Officer adoption in government: A topic model and structural equation modelling approach

Author

Listed:
  • Hui Zhang
  • Huiying Ding
  • Jianying Xiao

Abstract

With the generation of massive amounts of data, the Chief Data Officer (CDO) has been introduced in governments worldwide. Existing research on CDO is quite limited and primarily focuses on general descriptions of CDO. However, there is little research exploring the underlying reasons for the establishment of the CDO in government. To address this gap, this paper employs topic modeling to analyze government documents, identify factors influencing the adoption of CDO, and construct a research model. Data were collected from 277 employees within Chinese government organizations through a questionnaire survey and a quantitative analysis was performed to evaluate five hypotheses using structural equation modeling (SEM). The findings suggest that (1) data exploitation, data sharing and data management significantly influence data dividends, and (2) both data dividends and institutional pressures are key predictors of the intention to adopt the CDO, with digital dividends exerting a greater effect than institutional pressures.

Suggested Citation

  • Hui Zhang & Huiying Ding & Jianying Xiao, 2025. "Determinant factors of Chief Data Officer adoption in government: A topic model and structural equation modelling approach," PLOS ONE, Public Library of Science, vol. 20(8), pages 1-16, August.
    • Handle: RePEc:plo:pone00:0328683
    DOI: 10.1371/journal.pone.0328683
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0328683
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0328683&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0328683?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0328683. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.