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When to Lock the Volatile Input Price? Procurement of Commodity Components Under Different Pricing Schemes

Author

Listed:
  • Shi Chen

    (Michael G. Foster School of Business, University of Washington, Seattle, Washington 98195)

  • Junfei Lei

    (Michael G. Foster School of Business, University of Washington, Seattle, Washington 98195)

  • Kamran Moinzadeh

    (Michael G. Foster School of Business, University of Washington, Seattle, Washington 98195)

Abstract

Problem definition : We study a two-stage supply chain, where the supplier procures a key component to manufacture a product and the buyer orders from the supplier to meet a price-sensitive demand. As the input price is volatile, the two parties enter into either a standard contract, where the buyer orders just before the supplier starts production, or a time-flexible contract, where the buyer can lock a wholesale price in advance. Moreover, we consider three selling-price schemes: Market Driven, Cost Plus, and Profit Max. Academic/practical relevanc e: This problem is motivated by real practices in the cloud industry. Our model and optimization approach can address similar problems in other industries as well. Methodology : We assume that the input price follows a geometric Brownian motion. To determine the optimal ordering time, we propose an optimization approach that is different from the classic approach by Dixit et al. ( 1994 ) and Li and Kouvelis ( 1999 ). Our approach leads to deeper analytical results and more transparent ordering policy. Through a numerical experimentation, we compare profitability of different parties under different contracts, pricing schemes, and market conditions. Results : The buyer’s ordering policy is determined by a threshold policy based on the current time and input price; the optimal threshold depends on not only the drift and volatility of the input price but also, their relative magnitude. The supplier’s optimal procurement time should be determined by analyzing a trade-off between the holding cost of storing the components and the future input-price movement. Managerial implications : Under the Profit-Max and the Cost-Plus pricing schemes, the time-flexible contract is a Pareto improvement compared with the standard contract, whereas under the Market-Driven pricing scheme, the supplier may be better off under the standard contract. Moreover, although the most favorable scenario for the buyer is under the Profit-Max pricing scheme, the most favorable scenario for the supplier oftentimes is under the Cost-Plus pricing scheme. Furthermore, this study provides valuable insights into impacts of various characteristics of the component market, such as the trend and volatility of the input price, on the expected profit of the supply chain and its split between the two parties.

Suggested Citation

  • Shi Chen & Junfei Lei & Kamran Moinzadeh, 2022. "When to Lock the Volatile Input Price? Procurement of Commodity Components Under Different Pricing Schemes," Manufacturing & Service Operations Management, INFORMS, vol. 24(2), pages 1183-1201, March.
  • Handle: RePEc:inm:ormsom:v:24:y:2022:i:2:p:1183-1201
    DOI: 10.1287/msom.2021.0985
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    References listed on IDEAS

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    1. Gah-Yi Ban, 2020. "Confidence Intervals for Data-Driven Inventory Policies with Demand Censoring," Operations Research, INFORMS, vol. 68(2), pages 309-326, March.
    2. Ingersoll, Jonathan E, Jr & Ross, Stephen A, 1992. "Waiting to Invest: Investment and Uncertainty," The Journal of Business, University of Chicago Press, vol. 65(1), pages 1-29, January.
    3. René Caldentey & Martin B. Haugh, 2009. "Supply Contracts with Financial Hedging," Operations Research, INFORMS, vol. 57(1), pages 47-65, February.
    4. Chung-Lun Li & Panos Kouvelis, 1999. "Flexible and Risk-Sharing Supply Contracts Under Price Uncertainty," Management Science, INFORMS, vol. 45(10), pages 1378-1398, October.
    5. Pamela Pen-Erh Pei & David Simchi-Levi & Tunay I. Tunca, 2011. "Sourcing Flexibility, Spot Trading, and Procurement Contract Structure," Operations Research, INFORMS, vol. 59(3), pages 578-601, June.
    6. Panos Kouvelis & Rong Li & Qing Ding, 2013. "Managing Storable Commodity Risks: The Role of Inventory and Financial Hedge," Manufacturing & Service Operations Management, INFORMS, vol. 15(3), pages 507-521, July.
    7. Lenos Trigeorgis, 1993. "Real Options and Interactions With Financial Flexibility," Financial Management, Financial Management Association, vol. 22(3), Fall.
    8. Ankur Goel & Fehmi Tanrisever, 2017. "Financial Hedging and Optimal Procurement Policies under Correlated Price and Demand," Production and Operations Management, Production and Operations Management Society, vol. 26(10), pages 1924-1945, October.
    9. Pindyck, Robert S, 1988. "Irreversible Investment, Capacity Choice, and the Value of the Firm," American Economic Review, American Economic Association, vol. 78(5), pages 969-985, December.
    10. Nicholas C. Petruzzi & Maqbool Dada, 1999. "Pricing and the Newsvendor Problem: A Review with Extensions," Operations Research, INFORMS, vol. 47(2), pages 183-194, April.
    11. 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.
    12. Yimin Wang & Brian Tomlin, 2009. "To wait or not to wait: Optimal ordering under lead time uncertainty and forecast updating," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(8), pages 766-779, December.
    13. Marcus, Alan J & Modest, David M, 1984. "Futures Markets and Production Decisions," Journal of Political Economy, University of Chicago Press, vol. 92(3), pages 409-426, June.
    14. Sriram Dasu & José de la Torre, 1997. "Optimizing an International Network of Partially Owned Plants Under Conditions of Trade Liberalization," Management Science, INFORMS, vol. 43(3), pages 313-333, March.
    15. Ankur Goel & Genaro J. Gutierrez, 2011. "Multiechelon Procurement and Distribution Policies for Traded Commodities," Management Science, INFORMS, vol. 57(12), pages 2228-2244, December.
    16. D. J. Wu & Paul R. Kleindorfer, 2005. "Competitive Options, Supply Contracting, and Electronic Markets," Management Science, INFORMS, vol. 51(3), pages 452-466, March.
    17. Onur Boyabatlı & Paul R. Kleindorfer & Stephen R. Koontz, 2011. "Integrating Long-Term and Short-Term Contracting in Beef Supply Chains," Management Science, INFORMS, vol. 57(10), pages 1771-1787, October.
    18. Apostolos Burnetas & Stephen Gilbert, 2001. "Future Capacity Procurements Under Unknown Demand and Increasing Costs," Management Science, INFORMS, vol. 47(7), pages 979-992, July.
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