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Order Quantity and Timing Flexibility in Supply Chains: The Role of Demand Characteristics

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  • Joseph M. Milner

    (Joseph L. Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, Ontario, Canada M5S 3E6)

  • Panos Kouvelis

    (John M. Olin School of Business, Washington University, St. Louis, Missouri 63130)

Abstract

We study how differences in product demand characteristics affect the strategic value of different types of supply chain flexibility for accurate response. We propose a single-period inventory modelling framework with two ordering opportunities. The second order reflects updated demand information and potentially capitalizes on supply chain flexibility. We consider two complementary forms of flexibility: quantity flexibility in production and timing flexibility in scheduling. In this framework, we analyze the total inventory cost of a firm for alternate demand types. We model functional products through the standard assumption of independent demand over the period, fashion-driven innovative products through a Bayesian model, and innovative products with evolving demand through a Martingale process. The three demand processes exhibit very different behavior with respect to the value of the alternate forms of flexibility. We observe that quantity flexibility is of moderate value for functional goods and of high value for fashion-driven products for all lead times. Quantity flexibility is of low value for goods with evolving demand with long lead times but of high value for short lead times. Alternately, we observe timing flexibility is of highest value for functional goods, especially for cases of high holding cost, and is of lesser value for fashion-driven goods. It is of least value for goods with evolving demand. Both quantity and timing flexibility capabilities are required to significantly reduce the relevant supply chain costs for evolving-demand innovative goods when the lead times are long.

Suggested Citation

  • Joseph M. Milner & Panos Kouvelis, 2005. "Order Quantity and Timing Flexibility in Supply Chains: The Role of Demand Characteristics," Management Science, INFORMS, vol. 51(6), pages 970-985, June.
  • Handle: RePEc:inm:ormnsc:v:51:y:2005:i:6:p:970-985
    DOI: 10.1287/mnsc.1050.0359
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    References listed on IDEAS

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    9. 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.
    10. Nicholas G. Hall & Zhixin Liu, 2010. "Capacity Allocation and Scheduling in Supply Chains," Operations Research, INFORMS, vol. 58(6), pages 1711-1725, December.
    11. Bicer, Isik & Hagspiel, Verena, 2016. "Valuing quantity flexibility under supply chain disintermediation risk," International Journal of Production Economics, Elsevier, vol. 180(C), pages 1-15.
    12. Julia Miyaoka & Warren H. Hausman, 2008. "How Improved Forecasts Can Degrade Decentralized Supply Chains," Manufacturing & Service Operations Management, INFORMS, vol. 10(3), pages 547-562, July.
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    15. Minkyung Choy & Gunno Park, 2016. "Sustaining Innovative Success: A Case Study on Consumer-Centric Innovation in the ICT Industry," Sustainability, MDPI, vol. 8(10), pages 1-13, September.
    16. Khouja, Moutaz & Christou, Eliana & Stylianou, Antonis, 2020. "A heuristic approach to in-season capacity allocation in a multi-product newsvendor model," Omega, Elsevier, vol. 95(C).
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    20. Li, Tianyun & Fang, Weiguo & Baykal-Gürsoy, Melike, 2021. "Two-stage inventory management with financing under demand updates," International Journal of Production Economics, Elsevier, vol. 232(C).

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