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Dynamic Assortment with Demand Learning for Seasonal Consumer Goods

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  • Felipe Caro

    ()
    (Anderson School of Management, University of California, Los Angeles, California 90095)

  • Jérémie Gallien

    ()
    (Sloan School of Management, Massachusetts Institute of Technology, 30 Wadsworth Street, Cambridge, Massachusetts 02142)

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    Abstract

    Companies such as Zara and World Co. have recently implemented novel product development processes and supply chain architectures enabling them to make more product design and assortment decisions during the selling season, when actual demand information becomes available. How should such retail firms modify their product assortment over time in order to maximize overall profits for a given selling season? Focusing on a stylized version of this problem, we study a finite horizon multiarmed bandit model with several plays per stage and Bayesian learning. Our analysis involves the Lagrangian relaxation of weakly coupled dynamic programs (DPs), results contributing to the emerging theory of DP duality, and various approximations. It yields a closed-form dynamic index policy capturing the key exploration versus exploitation trade-off and associated suboptimality bounds. In numerical experiments its performance proves comparable to that of other closed-form heuristics described in the literature, but this policy is particularly easy to implement and interpret. This last feature enables extensions to more realistic versions of the motivating dynamic assortment problem that include implementation delays, switching costs, and demand substitution effects.

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    File URL: http://dx.doi.org/10.1287/mnsc.1060.0613
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 53 (2007)
    Issue (Month): 2 (February)
    Pages: 276-292

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    Handle: RePEc:inm:ormnsc:v:53:y:2007:i:2:p:276-292

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    Related research

    Keywords: retail assortment; dynamic programming duality; bayesian learning; multiarmed bandit;

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    Cited by:
    1. Tang, Christopher S., 2010. "A review of marketing-operations interface models: From co-existence to coordination and collaboration," International Journal of Production Economics, Elsevier, vol. 125(1), pages 22-40, May.
    2. Kevin Glazebrook & Joern Meissner & Jochen Schurr, 2012. "How big should my store be? On the interplay between shelf-space, demand learning and assortment decisions," Working Papers MRG/0021, Department of Management Science, Lancaster University, revised Dec 2012.
    3. Peter Jacko & Jose Nino-MOra, 2009. "An index for dynamic product promotion and the knapsack problem for perishable items," Statistics and Econometrics Working Papers ws093111, Universidad Carlos III, Departamento de Estadística y Econometría.

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