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Output Decision Under Demand Uncertainty with Stochastic Production Function: A Contingent Claims Approach

Author

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  • Kee H. Chung

    (Department of Finance, Fogelman College of Business and Economics, Memphis State University, Memphis, Tennessee 38152)

Abstract

This paper presents a contingent claims analysis of output decisions for the firm facing technological and demand uncertainty. The paper reveals that: (i) the optimal output level increases with the higher interest rate when the firm is subject to demand (and technological) uncertainty; (ii) the effect of demand volatility and production lead time on the optimal output level could be either positive or negative; (iii) the optimal project value decreases with the higher demand volatility; (iv) the optimal project value decreases with the longer production lead time when the firm is subject to demand uncertainty; and (v) the optimal project value decreases with the higher interest rate when the firm is subject to demand uncertainty; it increases with the higher interest rate, however, when the firm is subject to both demand and technological uncertainty. Some important managerial implications are discussed.

Suggested Citation

  • Kee H. Chung, 1990. "Output Decision Under Demand Uncertainty with Stochastic Production Function: A Contingent Claims Approach," Management Science, INFORMS, vol. 36(11), pages 1311-1328, November.
    • Handle: RePEc:inm:ormnsc:v:36:y:1990:i:11:p:1311-1328
    DOI: 10.1287/mnsc.36.11.1311
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    Citations

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    Cited by:

    1. Inmaculada Rodríguez-Puerta & Alberto Álvarez-López, 2016. "Optimal allocation of a fixed production under price uncertainty," Annals of Operations Research, Springer, vol. 237(1), pages 121-142, February.
    2. James A. Yunker & Dale Schofield, 2005. "Pricing training and development programs using stochastic CVP analysis," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 191-207.
    3. Inderfurth, Karl & Schefer, Rainer, 1996. "Analysis of order-up-to-S inventory policies under cash flow market value maximization," International Journal of Production Economics, Elsevier, vol. 46(1), pages 323-338, December.
    4. Zheng, Yanyan & Zhao, Yingxue & Wang, Nengmin & Meng, Xiaoge & Yang, Honglin, 2022. "Financing decision for a remanufacturing supply chain with a capital constrained retailer: A study from the perspective of market uncertainty," International Journal of Production Economics, Elsevier, vol. 245(C).
    5. Bardia Kamrad & Keith Ord, 2006. "Market risk and process uncertainty in production operations," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(7), pages 627-640, October.
    6. Soumyatanu Mukherjee & Sidhartha S. Padhi, 2022. "Sourcing decision under interconnected risks: an application of mean–variance preferences approach," Annals of Operations Research, Springer, vol. 313(2), pages 1243-1268, June.
    7. Pennings, Enrico & Natter, Martin, 2001. "Strategic diversification and capacity utilization," International Journal of Production Economics, Elsevier, vol. 72(3), pages 261-272, August.
    8. Tannous, George F. & Mangiameli, Paul M., 1996. "Adding features to a product: A micro-economic model," International Review of Economics & Finance, Elsevier, vol. 5(2), pages 149-173.
    9. Inmaculada Rodríguez-Puerta & Alberto A. Álvarez-López, 2016. "Optimal allocation of a fixed production under price uncertainty," Annals of Operations Research, Springer, vol. 237(1), pages 121-142, February.
    10. Driouchi, Tarik & Bennett, David & Simpson, Gary, 2010. "A path-dependent contingent-claims approach to capacity investments," European Journal of Operational Research, Elsevier, vol. 201(1), pages 319-323, February.

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