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Dynamic Inventory Control with Satisfaction-Dependent Demand

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  • Justin Azadivar
  • Max Shen
  • George Shanthikumar

Abstract

In this paper, we consider the discrete multiperiod newsvendor dynamic inventory control problem where customers follow a simple satisfaction-based demand process, where their probability of demand depends on whether their demand was satis ed the last time they demanded a product, and observe the differences between optimal policies and myopic policies which do not directly consider how inventory policies can affect future demand. We con rm the intuitive result that inventory managers should tend to order more than the myopic policy when satis ed customers are more likely to demand product, and less than the myopic policy when satis ed customers are less likely to demand. Moreover, we and that, when choosing a fixed order policy, even an empirically myopic solution with perfect demand distribution information will move away from the optimum towards a suboptimal solution.

Suggested Citation

  • Justin Azadivar & Max Shen & George Shanthikumar, 2010. "Dynamic Inventory Control with Satisfaction-Dependent Demand," Purdue University Economics Working Papers 1249, Purdue University, Department of Economics.
  • Handle: RePEc:pur:prukra:1249
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    File URL: https://business.purdue.edu/research/Working-papers-series/2010/1249.pdf
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    Cited by:

    1. Tianhu Deng & Zuo-Jun Max Shen & J. George Shanthikumar, 2014. "Statistical Learning of Service-Dependent Demand in a Multiperiod Newsvendor Setting," Operations Research, INFORMS, vol. 62(5), pages 1064-1076, October.

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