The Censored Newsvendor and the Optimal Acquisition of Information

Xiaomei Ding (), Martin L. Puterman () and Arnab Bisi ()
Additional contact information
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

Operations Research, 2002, vol. 50, issue 3, 517-527

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.

Keywords: Inventory/production: unknown demand; lost sales; censoring; optimal policies; Dynamic programming: Bayesian Markov decision processes (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (47)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:50:y:2002:i:3:p:517-527

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