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Hedging Commodity Procurement in a Bilateral Supply Chain

Author

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  • Danko Turcic

    (Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130)

  • Panos Kouvelis

    (Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130)

  • Ehsan Bolandifar

    (Chinese University of Hong Kong, Shatin, N.T., Hong Kong)

Abstract

This paper explores the merits of hedging stochastic input costs (i.e., reducing the risk of adverse changes in costs) in a decentralized, risk-neutral supply chain. Specifically, we consider a generalized version of the well-known “selling-to-the-newsvendor” model in which both the upstream and the downstream firms face stochastic input costs. The firms’ operations are intertwined—i.e., the downstream buyer depends on the upstream supplier for delivery and the supplier depends on the buyer for purchase. We show that if left unmanaged, the stochastic costs that reverberate through the supply chain can lead to significant financial losses. The situation could deteriorate to the point of a supply disruption if at least one of the supply chain members cannot profitably make its product. To the extent that hedging can ensure continuation in supply, hedging can have value to at least some of the members of the supply chain. We identify conditions under which the risk of the supply chain breakdown will cause the supply chain members to hedge their input costs: (i) the downstream buyer’s market power exceeds a critical threshold; or (ii) the upstream firm operates on a large margin, there is a high baseline demand for downstream firm’s final product, and the downstream firm’s market power is below a critical threshold. In absence of these conditions there are equilibria in which neither firm hedges. To sustain hedging in equilibrium, both firms must hedge and supply chain breakdown must be costly. The equilibrium hedging policy will (in general) be a partial hedging policy. There are also situations when firms hedge in equilibrium although hedging reduces their expected payoff.

Suggested Citation

  • Danko Turcic & Panos Kouvelis & Ehsan Bolandifar, 2015. "Hedging Commodity Procurement in a Bilateral Supply Chain," Manufacturing & Service Operations Management, INFORMS, vol. 17(2), pages 221-235, May.
  • Handle: RePEc:inm:ormsom:v:17:y:2015:i:2:p:221-235
    DOI: 10.1287/msom.2014.0514
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    References listed on IDEAS

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    Cited by:

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    2. Quansheng Lei & Zhelian Xu & Siqi Yang, 2019. "Research on Trade Credit and Bank Credit Based on Dynamic Inventory," Sustainability, MDPI, vol. 11(13), pages 1-29, June.
    3. Jiao Wang & Lima Zhao & Arnd Huchzermeier, 2021. "Operations‐Finance Interface in Risk Management: Research Evolution and Opportunities," Production and Operations Management, Production and Operations Management Society, vol. 30(2), pages 355-389, February.
    4. Wei Xing & Shanshan Ma & Xuan Zhao & Liming Liu, 2022. "Operational hedging or financial hedging? Strategic risk management in commodity procurement," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3233-3263, August.
    5. Volodymyr Babich & Panos Kouvelis, 2018. "Introduction to the Special Issue on Research at the Interface of Finance, Operations, and Risk Management (iFORM): Recent Contributions and Future Directions," Manufacturing & Service Operations Management, INFORMS, vol. 20(1), pages 1-18, February.
    6. Ni, Jian & Chu, Lap Keung & Li, Qiang, 2017. "Capacity decisions with debt financing: The effects of agency problem," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1158-1169.
    7. Panos Kouvelis & Danko Turcic, 2021. "Supporting Operations with Financial Hedging: Cash Hedging Vs. Cost Hedging in an Automotive Industry," Production and Operations Management, Production and Operations Management Society, vol. 30(3), pages 738-749, March.
    8. Wu, Desheng & Olson, David L. & Wang, Shouyang, 2019. "Finance-operations interface mechanism and models," Omega, Elsevier, vol. 88(C), pages 1-3.
    9. Niu, Baozhuang & Chu, Lap-Keung & Ni, Jian & Wang, Junwei, 2018. "Buy now and price later: Supply contracts with time-consistent mean–variance financial hedgingAuthor-Name: Li, Qiang," European Journal of Operational Research, Elsevier, vol. 268(2), pages 582-595.
    10. Sripad K. Devalkar & Ravi Anupindi & Amitabh Sinha, 2018. "Dynamic Risk Management of Commodity Operations: Model and Analysis," Manufacturing & Service Operations Management, INFORMS, vol. 20(2), pages 317-332, May.
    11. Sainathan, Arvind & Groenevelt, Harry, 2019. "Vendor managed inventory contracts – coordinating the supply chain while looking from the vendor’s perspective," European Journal of Operational Research, Elsevier, vol. 272(1), pages 249-260.
    12. Liu, Jing & Xia, Senmao & Wang, Zhaoxing & Nie, Jiajia & Ameen, Nisreen & Yan, Cheng & Lim, Ming K., 2023. "How to balance economic profits and environmental protection: The impacts of cash hedging on remanufacturing firms," International Journal of Production Economics, Elsevier, vol. 258(C).
    13. Bolandifar, Ehsan & Chen, Zhong, 2020. "Hedging through index-based price contracts in commodity-based supply chains," Omega, Elsevier, vol. 90(C).
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    15. S. Alex Yang & Nitin Bakshi & Christopher J. Chen, 2021. "Trade Credit Insurance: Operational Value and Contract Choice," Management Science, INFORMS, vol. 67(2), pages 875-891, February.
    16. Panos Kouvelis & Xiaole Wu & Yixuan Xiao, 2019. "Cash Hedging in a Supply Chain," Management Science, INFORMS, vol. 65(8), pages 3928-3947, August.
    17. Alavi Fard, Farzad & He, Jian & Ivanov, Dmitry & Jie, Ferry, 2019. "A utility adjusted newsvendor model with stochastic demand," International Journal of Production Economics, Elsevier, vol. 211(C), pages 154-165.
    18. Liao Wang, 2021. "Mean–Variance Hedging for Production Planning with Multiple Products," Production and Operations Management, Production and Operations Management Society, vol. 30(10), pages 3497-3522, October.

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