IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-770-0_7.html

Effects of Digital Training and Big Data Utilization on Innovation Creation in MSMEs by SECI Model

In: Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025)

Author

Listed:
  • Chenyi Ouyang

    (University College Dublin)

Abstract

The paper uses the method of quantitative study to investigate the effect of SECI model on the innovation ability of employees. The results show that (1) the digital training has positive influence on the innovation capacity of the staff; (2) the use of large data has a positive effect on the innovation capacity of the staff. This research can be used as a reference for the study of employee’s innovative ability, and it is significant to improve the innovation ability of the company. The findings are of great value to managers and researchers of MSMEs, and may guide the development of more efficient strategies to improve the performance of enterprises.

Suggested Citation

  • Chenyi Ouyang, 2025. "Effects of Digital Training and Big Data Utilization on Innovation Creation in MSMEs by SECI Model," Advances in Economics, Business and Management Research, in: Wenke Zang & Chunping Xia (ed.), Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025), pages 54-57, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6463-770-0_7
    DOI: 10.2991/978-94-6463-770-0_7
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:advbcp:978-94-6463-770-0_7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.