IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6239-701-9_41.html

China’s National Artificial Intelligence Strategy, Firm Adoption, and Short-Run Performance Effects

In: Proceedings of the 2026 11th International Conference on Social Sciences and Economic Development (ICSSED 2026)

Author

Listed:
  • Cheng Peng Cheong

    (Peking University, Guanghua School of Management)

Abstract

Artificial Intelligence (AI) is becoming increasingly important in firms’ performances. This paper examines how China’s 2017 national AI strategy affects firm-level AI adoption and its short-run performance implications. This study constructs AI adoption intensity by counting AI-related words using A-shared list firms within the time period 2001 to 2024. A two-way fixed effects model is introduced to study the relationship between degree of adopting AI and degree of how firms performed. Results are that the initiative is effective in incentivizing more AI adoption, but more adoption in AI does not mean better financial performance of firms at least in the short-run. It is found that there is a negative association between AI adoption and firm performances. Heterogeneity and moderating analyses are further conducted to explore the relationship under different firms’ characteristics. The findings contribute to the literature on the area of influences of China’s AI initiative on corporate AI adoption and its subsequent impact. Future researches could focus on mechanism analysis.

Suggested Citation

  • Cheng Peng Cheong, 2026. "China’s National Artificial Intelligence Strategy, Firm Adoption, and Short-Run Performance Effects," Advances in Economics, Business and Management Research, in: Joanna Rak & Md Rabiul Islam & Noralina Omar & Dragana Ostic (ed.), Proceedings of the 2026 11th International Conference on Social Sciences and Economic Development (ICSSED 2026), pages 397-404, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6239-701-9_41
    DOI: 10.2991/978-94-6239-701-9_41
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:advbcp:978-94-6239-701-9_41. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.