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Information Sharing Across Multiple Buyers In A Supply Chain

Author

Listed:
  • JIANGHUA WU

    (School of Business, Renmin University of China, Beijing 100872, China)

  • ANANTH IYER

    (Krannert School of Management, Purdue University, West Lafayette, Indiana 47907, USA)

  • PAUL V. PRECKEL

    (Department of Agricultural Economics, Purdue University, West Lafayette, Indiana 47907, USA)

  • XIN ZHAI

    (Guanghua School of Management, Peking University, Beijing 100871, China)

Abstract

We model the impact of information visibility in a two-level supply chain consisting of independent retailers who share upstream supply. The manufacturer supplies similar products to the two retailers and each retailer serves its independent end market. Retailers face one period of demand and satisfy the demand by ordering in the first period or back-ordering some of the demand and satisfying it in the second period. The wholesale price in the second period is decreasing in the total order size across the two retailers in the first period. This decrease in wholesale price captures the market learning effect of aggregate orders that has been extensively documented in empirical literature. We use a game-theoretic framework to investigate the ex-ante incentives for retailers to share their private demand information. We show that: (1) retailers have no incentives to share information about their private values when equilibrium order quantities are interior, i.e., the order size is between zero and the demand; (2) partial information sharing may be the equilibrium strategy for retailers when equilibrium order quantities are binding on the demand. Finally, numerical examples are provided for illustration. This paper thus identifies conditions under which different levels of information sharing may be the equilibrium outcomes in a supply chain.

Suggested Citation

  • Jianghua Wu & Ananth Iyer & Paul V. Preckel & Xin Zhai, 2012. "Information Sharing Across Multiple Buyers In A Supply Chain," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 29(01), pages 1-23.
    • Handle: RePEc:wsi:apjorx:v:29:y:2012:i:01:n:s0217595912400052
    DOI: 10.1142/S0217595912400052
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    References listed on IDEAS

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    Cited by:

    1. Bin Shen & Hau-Ling Chan, 2017. "Forecast Information Sharing for Managing Supply Chains in the Big Data Era: Recent Development and Future Research," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(01), pages 1-26, February.

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