IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v141y2025ics0140988324008302.html
   My bibliography  Save this article

Research on the impact of digital technology application in industry on industrial carbon dioxide emissions: Evidence from China

Author

Listed:
  • Liu, Jianjun
  • Liu, Mengting
  • Liang, Dapeng

Abstract

The application of digital technology (ADT) has become an inherent requirement for traditional industrial digitization transformation, and it provides a crucial driving force for reducing carbon dioxide (CO2) emissions in China’s industry. This study examines the impact of digital technology application in industry on industrial CO2 emissions, from both theoretical and empirical perspectives. Firstly, the model of endogenous economic growth with digital elements was extended, and it was found that the greater the degree of ADT in industry, the more it reduces CO2 emissions in equilibrium. Secondly, the study utilized panel data from 2011 to 2021, and the conclusions of the theoretical model were validated using a two-way fixed effects model, along with robustness and endogeneity tests. Thirdly, it was confirmed that public environmental concern acts as a moderator variable, enhancing the process of reducing industrial CO2 emissions through ADT. Lastly, the marginal effect of ADT on reducing industrial CO2 emissions initially increases and then decreases. At the 50th percentile level, the absolute value of the coefficient is the largest, indicating that at this point, ADT has the greatest marginal effect on reducing industrial CO2 emissions. Additionally, heterogeneous results show that ADT in less developed industrial regions has a stronger impact on carbon emission reduction compared to its application in more developed industrial regions.

Suggested Citation

  • Liu, Jianjun & Liu, Mengting & Liang, Dapeng, 2025. "Research on the impact of digital technology application in industry on industrial carbon dioxide emissions: Evidence from China," Energy Economics, Elsevier, vol. 141(C).
  • Handle: RePEc:eee:eneeco:v:141:y:2025:i:c:s0140988324008302
    DOI: 10.1016/j.eneco.2024.108121
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988324008302
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2024.108121?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 search for a different version of it.

    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:eneeco:v:141:y:2025:i:c:s0140988324008302. 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/eneco .

    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.