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The Censored Newsvendor and the Optimal Acquisition of Information

Author

Listed:
  • Xiaomei Ding

    (Pepsico Business Solution Group, 7701 Legacy Drive, Plano, Texas 75024-4099)

  • Martin L. Puterman

    (Faculty of Commerce and Business Administration, University of British Columbia, 2053 Main Mall, Vancouver, British Columbia, Canada V6T 1Z2)

  • Arnab Bisi

    (Faculty of Commerce and Business Administration, University of British Columbia, 2053 Main Mall, Vancouver, British Columbia, Canada V6T 1Z2)

Abstract

This paper investigates the effect of demand censoring on the optimal policy in newsvendor inventory models with general parametric demand distributions and unknown parameter values. We show that the newsvendor problem with observable lost sales reduces to a sequence of single-period problems, while the newsvendor problem with unobservable lost sales requires a dynamic analysis. Using a Bayesian Markov decision process approach we show that the optimalin ventory level in the presence of censored demand is higher than would be determined using a Bayesian myopic policy. We explore the economic rationality for this observation and illustrate it with numerical examples.

Suggested Citation

  • Xiaomei Ding & Martin L. Puterman & Arnab Bisi, 2002. "The Censored Newsvendor and the Optimal Acquisition of Information," Operations Research, INFORMS, vol. 50(3), pages 517-527, June.
    • Handle: RePEc:inm:oropre:v:50:y:2002:i:3:p:517-527
    DOI: 10.1287/opre.50.3.517.7752
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    References listed on IDEAS

    as
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