IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v57y2025i55p9245-9263.html

Does symbolic AI-related disclosure influence CEO promotion? Evidence from state-owned enterprises in China

Author

Listed:
  • Xin Wang
  • Tingting Zhao
  • Yue Sun
  • Dan Yang

Abstract

This paper considers firms’ artificial intelligence (AI)-related discretionary disclosure to examine whether symbolic communications of AI influences a CEO’s chance of career advancement in Chinese state-owned enterprises (SOEs). We find a positive relationship between symbolic AI disclosure and the possibility of managers getting promoted. Our main finding is more salient when a firm’s achievement of policy goals is more crucial, its financial performance is relatively poor, and a manager has more urgent promotion needs. Results imply that CEOs engage in impression management via managerial discretionary disclosure to strengthen organizational legitimacy and build a favourable impression, which may increase their probability of getting promoted.

Suggested Citation

  • Xin Wang & Tingting Zhao & Yue Sun & Dan Yang, 2025. "Does symbolic AI-related disclosure influence CEO promotion? Evidence from state-owned enterprises in China," Applied Economics, Taylor & Francis Journals, vol. 57(55), pages 9245-9263, November.
    • Handle: RePEc:taf:applec:v:57:y:2025:i:55:p:9245-9263
    DOI: 10.1080/00036846.2024.2412257
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00036846.2024.2412257
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00036846.2024.2412257?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

    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:taf:applec:v:57:y:2025:i:55:p:9245-9263. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    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.