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A Periodic Review Inventory Model with Demand Influenced by Promotion Decisions

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Author Info

  • Feng Cheng

    (IBM T. J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598)

  • Suresh P. Sethi

    (School of Management, University of Texas at Dallas, Box 830688, Richardson, Texas 75083)

Abstract

In this paper, we use a Markov decision process (MDP) to model the joint inventory-promotion decision problem. The state variable of the MDP represents the demand state brought about by changing environmental factors as well as promotion decisions. The demand state in a period determines the distribution of the random demand in that period. Optimal inventory and promotion decision policies in the finite horizon problem are obtained via dynamic programming. Under certain conditions, we show that there is a threshold inventory level P for each demand state such that if the threshold is exceeded, then it is desirable to promote the product. For the proportional ordering cost case, the optimal inventory replenishment policy is a base-stock type policy with the optimal base-stock level dependent on the promotion decision.

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File URL: http://dx.doi.org/10.1287/mnsc.45.11.1510
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Bibliographic Info

Article provided by INFORMS in its journal Management Science.

Volume (Year): 45 (1999)
Issue (Month): 11 (November)
Pages: 1510-1523

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Handle: RePEc:inm:ormnsc:v:45:y:1999:i:11:p:1510-1523

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Related research

Keywords: inventory model; Markov decision process; marketing; promotion; dynamic programming; finite horizon; base-stock policy; threshold policy;

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Cited by:
  1. Wei, Ying & Chen, Youhua (Frank), 2011. "Joint determination of inventory replenishment and sales effort with uncertain market responses," International Journal of Production Economics, Elsevier, vol. 134(2), pages 368-374, December.
  2. Toker Doganoglu & Daniel Klapper, 2006. "Goodwill and dynamic advertising strategies," Quantitative Marketing and Economics, Springer, vol. 4(1), pages 5-29, March.
  3. Taskin, Selda & Lodree Jr., Emmett J., 2010. "Inventory decisions for emergency supplies based on hurricane count predictions," International Journal of Production Economics, Elsevier, vol. 126(1), pages 66-75, July.

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