IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v90y2026ics1544612325025887.html

Digital finance and manufacturing innovation: Evidence from R&D investment and patent output in emerging economies

Author

Listed:
  • Wenjuan, Zhu

Abstract

In emerging economies, digital finance, as a technology driven innovation in financial services, is an important lever to leverage the growth of the real economy, while manufacturing innovation is the core of industrial upgrading, and its ability determines the level of economic development. This article focuses on the relationship between digital finance and manufacturing innovation, using R&D investment and patent output data from 10 typical manufacturing enterprises in 30 provinces of China from 2015 to 2023 as samples. A panel data model is used to construct a regression model, and the mediating effect is tested to explore the impact path of digital finance on manufacturing innovation. The results indicate that the breadth, depth of use, and degree of digitization of digital finance significantly promote innovation efficiency in the manufacturing industry. Among them, the depth of use has the strongest impact, while technological innovation and resource allocation optimization play a mediating role. Moreover, the higher the level of technological innovation, the stronger the empowering effect of digital finance. This verifies that digital finance can optimize R&D investment allocation, improve the quantity and quality of manufacturing patent output, and provide a basis for policy formulation.

Suggested Citation

  • Wenjuan, Zhu, 2026. "Digital finance and manufacturing innovation: Evidence from R&D investment and patent output in emerging economies," Finance Research Letters, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:finlet:v:90:y:2026:i:c:s1544612325025887
    DOI: 10.1016/j.frl.2025.109339
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612325025887
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2025.109339?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:90:y:2026:i:c:s1544612325025887. 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.