IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v102y2025ics1059056025005520.html
   My bibliography  Save this article

Analysis of the impact mechanisms of the digital economy and executive risk preference on the intelligent transformation of enterprises

Author

Listed:
  • Yang, Yuzhen
  • Tang, Mingfu

Abstract

This paper conducts an empirical analysis using sample data from Chinese listed companies between 2010 and 2023, examining the impact of the digital economy and executives' risk preferences on enterprises' intelligent transformation. The empirical results confirm that the digital economy significantly promotes enterprises' intelligent transformation; executives' risk preferences notably inhibit such transformation; the digital economy plays a moderating role in the relationship between executives' risk preferences and enterprises' intelligent transformation; the digital economy's impact on intelligent transformation demonstrates significant variability when contrasting heavily polluting enterprises with their lightly polluting counterparts; similarly, the impact of executives' risk preferences on intelligent transformation also shows heterogeneity between heavily polluting enterprises and lightly polluting enterprises.

Suggested Citation

  • Yang, Yuzhen & Tang, Mingfu, 2025. "Analysis of the impact mechanisms of the digital economy and executive risk preference on the intelligent transformation of enterprises," International Review of Economics & Finance, Elsevier, vol. 102(C).
    • Handle: RePEc:eee:reveco:v:102:y:2025:i:c:s1059056025005520
    DOI: 10.1016/j.iref.2025.104389
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056025005520
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.iref.2025.104389?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
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;

    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:eee:reveco:v:102:y:2025:i:c:s1059056025005520. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620165 .

    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.