IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i16p7273-d1722659.html
   My bibliography  Save this article

Does Artificial Intelligence Promote Sustainable Growth of Exporting Firms?

Author

Listed:
  • Xiulian Chen

    (School of Economics, Guangxi University, Nanning 530004, China)

  • Yanan Wu

    (School of Economics, Guangxi University, Nanning 530004, China)

  • Yangyang Long

    (School of Economics, Guangxi University, Nanning 530004, China)

Abstract

Against the backdrop of the accelerated development of the global digital economy and the deepening advancement of the sustainable development agenda, artificial intelligence (AI) is emerging as the core driving force behind the new round of technological revolution, reshaping the competitive landscape of international trade. Chinese export companies are facing dual pressures from technological barriers imposed by developed countries and cost competition from emerging economies, making traditional development models unsustainable. In this context, exploring how AI technology can promote the sustainable growth of export companies holds significant theoretical and practical significance. This article employs a three-dimensional fixed-effects nonlinear quadratic model to empirically analyze the dynamic relationship between AI adoption and the growth of export companies, based on data from Chinese A-share listed export companies. The analysis results show that AI has a significant dynamic nonlinear effect on the growth of export companies, which is initially inhibitory and then becomes promotional. In the early stages, due to high technology adaptation costs, company growth is somewhat inhibited. However, as the technology matures, AI significantly enhances the company’s innovation capabilities and competitiveness, thereby promoting its long-term sustainable growth. This result remains valid after a series of robustness tests. This effect is significant in non-state-owned enterprises and medium-to-low technology industries, but not in state-owned enterprises and high-technology industries. Three pathways—enterprise efficiency, innovation investment, and levels of digital factor investment—enhance this dynamic effect. Finally, based on the above research findings, this study proposes policy recommendations for enterprises to leverage artificial intelligence technology to promote the growth of export companies.

Suggested Citation

  • Xiulian Chen & Yanan Wu & Yangyang Long, 2025. "Does Artificial Intelligence Promote Sustainable Growth of Exporting Firms?," Sustainability, MDPI, vol. 17(16), pages 1-23, August.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7273-:d:1722659
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/16/7273/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/16/7273/
    Download Restriction: no
    ---><---

    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:gam:jsusta:v:17:y:2025:i:16:p:7273-:d:1722659. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.