IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2025i13p2184-d1694765.html
   My bibliography  Save this article

Sales Mode Selection and Blockchain Adoption for Platform Supply Chain Under Risk Aversion

Author

Listed:
  • Yu Jing

    (School of Business, Soochow University, Suzhou 215021, China)

  • Fengzhi Liu

    (College of Economic and Social Development, Nankai University, Tianjin 300071, China)

Abstract

Uncertainty in consumer purchasing behavior within online markets propels manufacturers to adopt blockchain for risk mitigation, reshaping supply chain operational dynamics. This study investigates the sales mode selection and blockchain adoption strategies of a risk-averse manufacturer in platform supply chain under uncertain market demand. By integrating Stackelberg game theory with mean-variance analysis, we analyze supply chain equilibrium across four scenarios: RN, RB, AN, and AB. Our findings highlight the significance of a critical commission rate threshold in the manufacturer’s sales mode choice, emphasizing that blockchain adoption enhances the preference for the agency mode. Importantly, highly risk-averse manufacturers are inclined to absorb higher costs associated with blockchain adoption, while those with lower risk aversion only consider it when costs are minimal. Notably, the “agency mode with blockchain adoption” (AB) creates mutual benefits under low adoption costs and risk aversion. When both parties exhibit risk aversion, the platform’s risk aversion significantly influences resale-mode decisions, leading to a transition from the scenario AN to the RB, thereby optimizing synchronized profits.

Suggested Citation

  • Yu Jing & Fengzhi Liu, 2025. "Sales Mode Selection and Blockchain Adoption for Platform Supply Chain Under Risk Aversion," Mathematics, MDPI, vol. 13(13), pages 1-23, July.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:13:p:2184-:d:1694765
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/13/2184/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/13/13/2184/
    Download Restriction: no
    ---><---

    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:gam:jmathe:v:13:y:2025:i:13:p:2184-:d:1694765. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.