IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v15y2025i3p21582440251357382.html
   My bibliography  Save this article

How Does Government Attention Enhance Regional Innovation Performance From the Perspective of Innovation-driven Productivity?

Author

Listed:
  • Sheng Chen
  • Heng Yang
  • Jie Li

Abstract

The concept of innovation-driven productivity is a crucial factor in fostering high-quality economic development, grounded in economic theories and practices from the past several decades. This study utilizes machine learning to develop an innovation-driven productivity dictionary and conducts text analysis on 390 government work reports from 30 provinces spanning 2011 to 2023. This analysis constructs an indicator of government attention to innovation-driven productivity at the governmental level. The findings indicate that attention to innovation-driven productivity significantly enhances regional innovation performance, a conclusion that remains robust across various tests. Mechanistically, government attention to innovation-driven productivity promotes the development of productive services and increases enterprise innovation investment, thereby boosting regional innovation performance. According to heterogeneity research, western regions see a far greater impact from government attention on fostering innovative performance than do central and eastern regions. In terms of manufacturing levels, regions with lower manufacturing levels experience a greater positive impact from government attention than those with higher manufacturing levels. Regarding the degree of policy intervention, the effects during periods of high intervention are significantly stronger than those observed during periods of low intervention. This study offers useful suggestions for how governments can successfully use innovation-driven productivity to promote regional innovation development in addition to broadening the theoretical framework of the relationship between governmental actions and regional innovation performance. JEL classification: O00 O38 C23 C60

Suggested Citation

  • Sheng Chen & Heng Yang & Jie Li, 2025. "How Does Government Attention Enhance Regional Innovation Performance From the Perspective of Innovation-driven Productivity?," SAGE Open, , vol. 15(3), pages 21582440251, September.
  • Handle: RePEc:sae:sagope:v:15:y:2025:i:3:p:21582440251357382
    DOI: 10.1177/21582440251357382
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440251357382
    Download Restriction: no

    File URL: https://libkey.io/10.1177/21582440251357382?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • O00 - Economic Development, Innovation, Technological Change, and Growth - - General - - - General
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

    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:sae:sagope:v:15:y:2025:i:3:p:21582440251357382. 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: SAGE Publications (email available below). General contact details of provider: .

    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.