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A delayed demand supply chain: Incentives for upstream players

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  • Hosoda, Takamichi
  • Disney, Stephen M.

Abstract

We study a decentralized supply chain where only delayed market demand information is available for making replenishment decisions. The impact of this delay is quantified in a serially linked two-level supply chain where each player exploits the order-up-to replenishment policy. The market demand is assumed to be a first-order autoregressive process. It is shown that the first level of the supply chain benefits from shorter time delays; however, the benefit for the second level is quite minor at best and can sometimes even be (counter-intuitively) detrimental. We conclude that the second level does not have a strong incentive to reduce the time delays in the shared market demand information.

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  • Hosoda, Takamichi & Disney, Stephen M., 2012. "A delayed demand supply chain: Incentives for upstream players," Omega, Elsevier, vol. 40(4), pages 478-487.
    • Handle: RePEc:eee:jomega:v:40:y:2012:i:4:p:478-487
    DOI: 10.1016/j.omega.2011.09.005
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    Cited by:

    1. Balachandran, Kashi R. & Wang, Hsiao-Wen & Li, Shu-Hsing & Wang, Taychang, 2013. "In-house capability and supply chain decisions," Omega, Elsevier, vol. 41(2), pages 473-484.
    2. Hoberg, Kai & Thonemann, Ulrich W., 2014. "Modeling and analyzing information delays in supply chains using transfer functions," International Journal of Production Economics, Elsevier, vol. 156(C), pages 132-145.
    3. Li, Xiang & Li, Yongjian & Cai, Xiaoqiang, 2012. "A note on the random yield from the perspective of the supply chain," Omega, Elsevier, vol. 40(5), pages 601-610.
    4. Wang, Xun & Disney, Stephen M. & Wang, Jing, 2014. "Exploring the oscillatory dynamics of a forbidden returns inventory system," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 3-12.
    5. Chatfield, Dean C. & Pritchard, Alan M., 2013. "Returns and the bullwhip effect," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 159-175.
    6. Ali, Mohammad M. & Babai, Mohamed Zied & Boylan, John E. & Syntetos, A.A., 2017. "Supply chain forecasting when information is not shared," European Journal of Operational Research, Elsevier, vol. 260(3), pages 984-994.
    7. Petropoulos, Fotios & Wang, Xun & Disney, Stephen M., 2019. "The inventory performance of forecasting methods: Evidence from the M3 competition data," International Journal of Forecasting, Elsevier, vol. 35(1), pages 251-265.
    8. Kovalyov, Mikhail Y. & Pesch, Erwin, 2014. "A game mechanism for single machine sequencing with zero risk," Omega, Elsevier, vol. 44(C), pages 104-110.
    9. Fang, Xin & Zhang, Cheng & Robb, David J. & Blackburn, Joseph D., 2013. "Decision support for lead time and demand variability reduction," Omega, Elsevier, vol. 41(2), pages 390-396.
    10. Dominguez, Roberto & Cannella, Salvatore & Barbosa-Póvoa, Ana P. & Framinan, Jose M., 2018. "OVAP: A strategy to implement partial information sharing among supply chain retailers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 110(C), pages 122-136.

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