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Does a Manufacturer Benefit from Selling to a Better-Forecasting Retailer?

Author

Listed:
  • Terry A. Taylor

    () (Haas School of Business, University of California, Berkeley, Berkeley, California 94720)

  • Wenqiang Xiao

    () (Stern School of Business, New York University, New York, New York 10012)

Abstract

This paper considers a manufacturer selling to a newsvendor retailer that possesses superior demand-forecast information. We show that the manufacturer's expected profit is convex in the retailer's forecasting accuracy: The manufacturer benefits from selling to a better-forecasting retailer if and only if the retailer is already a good forecaster. If the retailer has poor forecasting capabilities, then the manufacturer is hurt as the retailer's forecasting capability improves. More generally, the manufacturer tends to be hurt (benefit) by improved retailer forecasting capabilities if the product economics are lucrative (poor). Finally, the optimal procurement contract is a quantity discount contract.

Suggested Citation

  • Terry A. Taylor & Wenqiang Xiao, 2010. "Does a Manufacturer Benefit from Selling to a Better-Forecasting Retailer?," Management Science, INFORMS, vol. 56(9), pages 1584-1598, September.
  • Handle: RePEc:inm:ormnsc:v:56:y:2010:i:9:p:1584-1598
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    File URL: http://dx.doi.org/10.1287/mnsc.1100.1204
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Zhao, Xuan & Xing, Wei & Liu, Liming & Wang, Shouyang, 2015. "Demand information and spot price information: Supply chains trading in spot markets," European Journal of Operational Research, Elsevier, vol. 246(3), pages 837-849.
    2. Choi, Tsan-Ming, 2013. "Local sourcing and fashion quick response system: The impacts of carbon footprint tax," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 55(C), pages 43-54.
    3. Huang, Song & Yang, Jun, 2016. "Information acquisition and transparency in a supply chain with asymmetric production cost information," International Journal of Production Economics, Elsevier, vol. 182(C), pages 449-464.
    4. Hosoda, Takamichi & Disney, Stephen M., 2012. "A delayed demand supply chain: Incentives for upstream players," Omega, Elsevier, vol. 40(4), pages 478-487.
    5. Fleischhacker, Adam J. & Fok, Pak-Wing, 2015. "On the relationship between entropy, demand uncertainty, and expected loss," European Journal of Operational Research, Elsevier, vol. 245(2), pages 623-628.
    6. Eksoz, Can & Mansouri, S. Afshin & Bourlakis, Michael, 2014. "Collaborative forecasting in the food supply chain: A conceptual framework," International Journal of Production Economics, Elsevier, vol. 158(C), pages 120-135.

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