IDEAS home Printed from https://ideas.repec.org/a/taf/veecee/v28y2026i1p119-136.html

The impact mechanism of entrepreneurial competency and entrepreneurial model matching on entrepreneurial performance

Author

Listed:
  • Liying Lei

Abstract

From the perspective of matching, this paper explores the impact mechanism of entrepreneurial competency and entrepreneurial model matching on entrepreneurial performance. Then this paper uses cluster analysis and independent sample t-test to carry out the empirical analysis. The research results show the following relationship. (1) Entrepreneurs whose risk aversion psychology, entrepreneurial learning cognition, organizational management functions, and genetic network application capabilities are matched with survival-driven entrepreneurial models can improve the survival performance of new ventures. (2) Entrepreneurs whose risk propensity psychology, knowledge conversion cognition, strategic decision-making functions, and industrial network application capabilities are matched with the opportunity-driven entrepreneurial model, which can improve the survival and growth performance of new ventures. (3) Entrepreneurs’ self-potency psychology, technology transformation cognition, R&D innovation function, and network management capabilities are matched with the innovation-driven entrepreneurial model, which can improve the innovation performance of new ventures. Through empirical analysis, it was found that there were 22 matching samples, accounting for 61.11% of samples. There were 14 mismatched samples, accounting for 38.89% of samples, indicating a higher matching degree between entrepreneurial capability cluster and innovation-driven entrepreneurial model.

Suggested Citation

  • Liying Lei, 2026. "The impact mechanism of entrepreneurial competency and entrepreneurial model matching on entrepreneurial performance," Venture Capital, Taylor & Francis Journals, vol. 28(1), pages 119-136, January.
  • Handle: RePEc:taf:veecee:v:28:y:2026:i:1:p:119-136
    DOI: 10.1080/13691066.2023.2265564
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13691066.2023.2265564
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/13691066.2023.2265564?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

    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:taf:veecee:v:28:y:2026:i:1:p:119-136. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TVEC20 .

    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.