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Title: Opportunity loss minimization and newsvendor behavior
Authors: Xu, XS
Yan, H 
Chan, CK 
Issue Date: 2017
Source: Discrete dynamics in nature and society, 2017, v. 2017, 3481869
Abstract: To study the decision bias in newsvendor behavior, this paper introduces an opportunity loss minimization criterion into the newsvendor model with backordering. We apply the Conditional Value-at-Risk (CVaR) measure to hedge against the potential risks from newsvendor's order decision. We obtain the optimal order quantities for a newsvendor to minimize the expected opportunity loss and CVaR of opportunity loss. It is proven that the newsvendor's optimal order quantity is related to the density function of market demand when the newsvendor exhibits risk-averse preference, which is inconsistent with the results in Schweitzer and Cachon (2000). The numerical example shows that the optimal order quantity that minimizes CVaR of opportunity loss is bigger than expected profit maximization (EPM) order quantity for high-profit products and smaller than EPM order quantity for low-profit products, which is different from the experimental results in Schweitzer and Cachon (2000). A sensitivity analysis of changing the operation parameters of the two optimal order quantities is discussed. Our results confirm that high return implies high risk, while low risk comes with low return. Based on the results, some managerial insights are suggested for the risk management of the newsvendor model with backordering.
Publisher: Hindawi Publishing Corporation
Journal: Discrete dynamics in nature and society 
ISSN: 1026-0226
EISSN: 1607-887X
DOI: 10.1155/2017/3481869
Rights: Copyright © 2017 Xinsheng Xu et al.This is an open access article distributed under the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The following publication Xinsheng Xu, Hong Yan, Chi Kin Chan, "Opportunity Loss Minimization and Newsvendor Behavior", Discrete Dynamics in Nature and Society, vol. 2017, Article ID 3481869, 11 pages, 2017 is available at
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