The censored newsvendor and the optimal acquisition of information
成果类型：
Article
署名作者：
Ding, XM; Puterman, ML; Bisi, A
署名单位：
PepsiCo; University of British Columbia
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.50.3.517.7752
发表日期：
2002
页码：
517-527
关键词：
摘要：
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 optimal inventory 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.