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Advance Demand Information in a Multiproduct System

Author

Listed:
  • Fernando Bernstein

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • Gregory A. DeCroix

    (Wisconsin School of Business, University of Wisconsin–Madison, Madison, Wisconsin 53706)

Abstract

In this paper we examine the impact of different types of advance demand information on firm profit and on the benefits of resource flexibility. Specifically, we consider a firm that must choose capacities of resources that will be used to satisfy stochastic demand for multiple products, where demands follow a multivariate normal distribution. Prior to the capacity decision, the firm receives information revealing either the total volume of demand across products or the mix of demand between products. We examine two different scenarios: a dedicated resource setting with product-specific resources and a common resource scenario with one flexible resource. For both scenarios we derive the distribution of the (possibly imperfect) volume or mix demand signal, as well as the conditional distributions of demand given the particular signal. We explore the impact of either type of information on optimal capacities and profit. We find that commonality and volume information are strategic complements—so that it is more valuable to obtain volume information in settings with a common resource. On the other hand, commonality and mix information are strategic substitutes. Moreover, we find that mix and volume information themselves are complements in systems with dedicated resources. Having either type of information is valuable in reducing uncertainty for each individual product demand, but having both of them together provides information on two different dimensions, allowing for a much greater reduction in demand uncertainty. In systems with a common resource, however, the two types of information are substitutes. Because volume information is well aligned with commonality (both focus on total demand), such information already provides much of the value that can be obtained—having mix information adds limited additional value.

Suggested Citation

  • Fernando Bernstein & Gregory A. DeCroix, 2015. "Advance Demand Information in a Multiproduct System," Manufacturing & Service Operations Management, INFORMS, vol. 17(1), pages 52-65, February.
  • Handle: RePEc:inm:ormsom:v:17:y:2015:i:1:p:52-65
    DOI: 10.1287/msom.2014.0502
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    References listed on IDEAS

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    2. Viktoryia Buhayenko & Dick den Hertog, 2017. "Adjustable Robust Optimisation approach to optimise discounts for multi-period supply chain coordination under demand uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 55(22), pages 6801-6823, November.
    3. Rippe, Christoph & Kiesmüller, Gudrun P., 2023. "The repair kit problem with imperfect advance demand information," European Journal of Operational Research, Elsevier, vol. 304(2), pages 558-576.
    4. Oguzhan Vicil, 2021. "Optimizing stock levels for service-differentiated demand classes with inventory rationing and demand lead times," Flexible Services and Manufacturing Journal, Springer, vol. 33(2), pages 381-424, June.
    5. Du, Bisheng & Larsen, Christian, 2017. "Reservation policies of advance orders in the presence of multiple demand classes," European Journal of Operational Research, Elsevier, vol. 256(2), pages 430-438.
    6. Christoph Rippe & Gudrun P. Kiesmüller, 2023. "The added value of advance demand information for the planning of a repair kit," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(1), pages 311-335, March.
    7. Jana Ralfs & Gudrun P. Kiesmüller, 2022. "Inventory management with advance demand information and flexible shipment consolidation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1009-1044, December.

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