Many theoretical models adopt a normative approach and assume that decision makers are perfect optimizers. In contrast, this paper takes a descriptive approach and considers bounded rationality, in the sense that decision makers are prone to errors and biases. Our decision model builds on the quantal choice model: While the best decision need not always be made, better decisions are made more often. We apply this framework to the classic newsvendor model and characterize the ordering decisions made by a boundedly rational decision maker. We identify systematic biases and offer insight into when overordering and underordering may occur. We also investigate the impact of these biases on several other inventory settings that have traditionally been studied using the newsvendor model as a building block, such as supply chain contracting, the bullwhip effect, and inventory pooling. We find that incorporating decision noise and optimization error yields results that are consistent with some anomalies highlighted by recent experimental findings.Keywords bounded rationality, newsvendor, logit choice, random utility, quantal response, supply chain, bullwhip effect, inventory, pooling
DisciplinesOperations and Supply Chain Management | Other Business | Policy History, Theory, and Methods
CommentsAt the time of publication, author Xuanming Su was affiliated with the University of California. Currently ( July 2016), he is a faculty member in the Operation, Information and Decisions Department of the Wharton School at the University of Pennsylvania.This journal article is available at ScholarlyCommons: http://repository.upenn.edu/oid_papers/140Electronic copy available at: http://ssrn.com/abstract=944155
Bounded Rationality in Newsvendor Models
Xuanming SuHaas School of Business, University of California, Berkeley, CA 94720, USA xuanming@haas.berkeley.edu Many theoretical models adopt a normative approach and assume that decision-makers are perfect optimizers. In contrast, this paper takes a descriptive approach and considers bounded rationality, in the sense that decision-makers are prone to errors and biases. Our decision model builds upon the quantal choice model: while the best decision need not always be made, better decisions are made more often. We apply this framework to the classic newsvendor model and characterize the ordering decisions made by a boundedly rational decision-maker. We identify systematic biases and offer insight into when over-ordering and under-ordering may occur. We also investigate the impact of these biases on several other inventory settings that have traditionally been studied using the newsvendor model as a building block, such as supply chain contracting, the bullwhip effect, and inventory pooling. We find that incorporating decision noise and optimization error yields results that are consistent with some anomalies highlighted by recent experimental findings.