IDEAS home Printed from https://ideas.repec.org/h/spr/advbcp/978-94-6463-256-9_25.html

A Study on Benefit Distribution in the Supply Chain of Sericulture Industry Based on Shapley’s Value Method

In: Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)

Author

Listed:
  • Chunxue Yu

    (Jiangsu University of Science and Technology, School of Economics and Management)

  • Guangming Zhang

    (Jiangsu University of Science and Technology, School of Economics and Management)

Abstract

At present, there is an imbalance between income and expenditure in the sericulture supply chain, and the income does not cover the expenditure. At the same time, the supply chain of the sericulture industry has a single cooperative relationship among all the subjects and does not form a whole. In this paper, we use the sericulture research institute, sericulture seed farms and sericulture farmers (cooperatives) as the main research objects, and use the shapley value method to measure the profit distribution of one sericulture seed among each subject based on the contribution degree of different subjects, and make suggestions to promote the change of cooperation mode of each subject in the sericulture seed industry supply chain and the stable development of the supply chain. It is hoped that the above problems can be solved by changing the mode of cooperation among the main actors in the sericulture supply chain, integrating resources, sharing the production costs of the main actors in the supply chain and increasing the profits of the supply chain.

Suggested Citation

  • Chunxue Yu & Guangming Zhang, 2024. "A Study on Benefit Distribution in the Supply Chain of Sericulture Industry Based on Shapley’s Value Method," Advances in Economics, Business and Management Research, in: Suhaiza Hanim Binti Dato Mohamad Zailani & Kosga Yagapparaj & Norhayati Zakuan (ed.), Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023), pages 241-247, Springer.
  • Handle: RePEc:spr:advbcp:978-94-6463-256-9_25
    DOI: 10.2991/978-94-6463-256-9_25
    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:978-94-6463-256-9_25. 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.