IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v102y2025ics1057521925002030.html
   My bibliography  Save this article

Digital transformation and tax compliance in Chinese industrial sector

Author

Listed:
  • Chen, Shi
  • Liu, Zhongyi
  • Cai, Wanlin

Abstract

This study examines the complex relationship between digital technology adoption and corporate tax compliance from a signaling theory perspective, focusing on the Chinese industrial sector. Using the propensity score matching difference-in-differences method, this study identifies a negative correlation between digital technology adoption and adherence to tax regulations. Although digital tools improve transparency and data accuracy, they also introduce complexities that create greater opportunities for tax evasion. Findings emphasize the need for a favorable signaling environment, characterized by strong regulatory frameworks and clear communication channels, to mitigate these risks and promote compliance. This study argues that the tax system must evolve alongside the digital economy and fully leverage digital tools to enhance tax administration. By examining how technological advancements interact with regulatory practices to shape corporate behavior. Insights presented offer valuable guidance for policymakers seeking to strengthen regulatory frameworks and effectively integrate digital advancements to improve tax compliance. Ultimately, this study provides actionable recommendations for enhancing compliance through the strategic application of digital technology within institutional structures.

Suggested Citation

  • Chen, Shi & Liu, Zhongyi & Cai, Wanlin, 2025. "Digital transformation and tax compliance in Chinese industrial sector," International Review of Financial Analysis, Elsevier, vol. 102(C).
    • Handle: RePEc:eee:finana:v:102:y:2025:i:c:s1057521925002030
    DOI: 10.1016/j.irfa.2025.104116
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521925002030
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.irfa.2025.104116?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:finana:v:102:y:2025:i:c:s1057521925002030. 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/inca/620166 .

    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.