IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v54y2016i5p1322-1333.html
   My bibliography  Save this article

Trust in supply forecast information sharing

Author

Listed:
  • Fatemeh Firouzi
  • Mohamad Y. Jaber
  • Enzo Baglieri

Abstract

In this paper, we investigate the role of trust in supply forecast signalling in a supply chain with a supplier and a manufacturer in a one-shot game. It is assumed that the supplier faces a random yield uncertainty that is multiplied by the manufacturer’s order quantity. The supplier has a private forecast of yield risk. Based on the information, the supplier decides whether to share its forecast truthfully, or not to share. On the other hand, the manufacturer is faced with two ordering strategies. If it trusts the supplier’s report, then it updates its belief on the yield risk providing a forecast signal by the supplier. Otherwise, it orders based on its prior belief. We analytically obtain the optimal order quantity where the random yield uncertainty follows uniform distribution. The intuitive result indicates that the supplier has a tendency to deviate from reporting true forecast information. The numerical results support the intuitive conclusion.

Suggested Citation

  • Fatemeh Firouzi & Mohamad Y. Jaber & Enzo Baglieri, 2016. "Trust in supply forecast information sharing," International Journal of Production Research, Taylor & Francis Journals, vol. 54(5), pages 1322-1333, March.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:5:p:1322-1333
    DOI: 10.1080/00207543.2015.1068961
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2015.1068961
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2015.1068961?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Baofeng & Wu, Desheng Dash & Liang, Liang, 2018. "Trade credit model with customer balking and asymmetric market information," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 31-46.
    2. De Giovanni, Pietro, 2020. "Blockchain and smart contracts in supply chain management: A game theoretic model," International Journal of Production Economics, Elsevier, vol. 228(C).

    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:tprsxx:v:54:y:2016:i:5:p:1322-1333. 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/TPRS20 .

    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.