IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v79y2025ics106294082500083x.html
   My bibliography  Save this article

The optimal timing and conditions for the digital transformation of traditional enterprises

Author

Listed:
  • Chen, Zhuming
  • Liang, Wanhua

Abstract

By taking data as the core factor of production, reconstructing the corporate value function after digital transformation and using in real option game theory, this paper provides an analytical formula for the optimal timing of the digital transformation of traditional corporations, the value functions of leader corporations and follower corporations and the optimal timing of digital transformation. This study identifies at least 11 factors that influence the optimal timing of transition. The study shows that the greater the cost of transformation investment, the higher the expected return of the enterprise is, the higher the marginal cost of production of the enterprise, the slower the digital transformation, and the longer the interval between the digital transformation of the follower after the transformation of the leader. Usually, the optimal time for the digital transformation of large enterprises is earlier than that of small and medium-sized enterprises. The more data elements an enterprise generates, the better the growth of the industry and the data element market, the higher the volatility, the faster the transformation, and the shorter the transition time between leaders and followers.

Suggested Citation

  • Chen, Zhuming & Liang, Wanhua, 2025. "The optimal timing and conditions for the digital transformation of traditional enterprises," The North American Journal of Economics and Finance, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:ecofin:v:79:y:2025:i:c:s106294082500083x
    DOI: 10.1016/j.najef.2025.102443
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S106294082500083X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2025.102443?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:ecofin:v:79:y:2025:i:c:s106294082500083x. 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/620163 .

    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.