IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v88y2026ics154461232502152x.html

Research on artificial intelligence enabling green development from the perspective of enterprise green innovation

Author

Listed:
  • Hao, Linxiao
  • Yuan, Jinyu
  • Deng, Siwei
  • Zhi, Zhonghe

Abstract

This study analyzes how artificial intelligence (AI) development fosters corporate green development using data from Chinese listed firms (2010–2023). Results indicate that AI significantly enhances green development, particularly in technology-driven, high-tech, and growth-stage enterprises. Green innovation (quantity and quality) mediates this relationship, while internal control positively moderates it, unlike regional environmental regulation. AI facilitates green development through innovation enhancement and resource optimization. Policy implications include targeted AI research and development support for key sectors, establishing green innovation ecosystems, and strengthening corporate governance to ensure effective AI implementation to advance sustainable economic growth.

Suggested Citation

  • Hao, Linxiao & Yuan, Jinyu & Deng, Siwei & Zhi, Zhonghe, 2026. "Research on artificial intelligence enabling green development from the perspective of enterprise green innovation," Finance Research Letters, Elsevier, vol. 88(C).
  • Handle: RePEc:eee:finlet:v:88:y:2026:i:c:s154461232502152x
    DOI: 10.1016/j.frl.2025.108899
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S154461232502152X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2025.108899?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:finlet:v:88:y:2026:i:c:s154461232502152x. 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/frl .

    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.