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Newsvendor models and biases under ambiguity
Published in IEOM Society
2019
Volume: 2019
   
Issue: MAR
Pages: 3105 - 3105
Abstract
In this study, we model the classical newsvendor ordering preferences under ambiguity. The extant literature on normative models in the newsvendor setting assumes decision-making under risk, where decision-maker has exact knowledge of the probabilities associated with the outcomes. In several business situations, the demand distribution is often incomplete or unknown. This results in decision-making under ambiguous situations. Decision theory recognizes the difference between exact probabilities and more realistic ambiguous probabilities. In his seminal paper, Scarf (1958) develops a max-min approach for the newsvendor with incomplete demand information. In the Scarf model, the newsvendor is assumed to be risk-neutral and ambiguity averse. In the recent experimental literature, it has been observed that the newsvendor behavior is not consistent with the Scarf model, and exhibits pull-to- center bias and other biases. This motivates our research to develop quantitative models under ambiguity to describe the observed biases in the literature. © IEOM Society International.
About the journal
JournalProceedings of the International Conference on Industrial Engineering and Operations Management
PublisherIEOM Society
ISSN21698767
Open AccessNo