The Loss-Averse Newsvendor Problem with Random Yield and Reference Dependence

Wei Liu, Shiji Song, Ying Qiao, Han Zhao and Huachang Wang
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Wei Liu: Department of Basic Science, Wuhan Donghu University, Wuhan 430212, China
Shiji Song: Department of Automation, Tsinghua University, Beijing 100084, China
Ying Qiao: Financial Department, Wuhan Business University, Wuhan 430056, China
Han Zhao: Department of Basic Science, Army Logistics University, Chongqing 401311, China
Huachang Wang: Department of Basic Science, Army Logistics University, Chongqing 401311, China

Mathematics, 2020, vol. 8, issue 8, 1-15

Abstract: This paper studies a loss-averse newsvendor problem with reference dependence, where both demand and yield rate are stochastic. We obtain the loss-averse newsvendor’s optimal ordering policy and analyze the effects of loss aversion, reference dependence, random demand and yield on it. It is shown that the loss-averse newsvendor’s optimal order quantity and expected utility decreases in loss aversion level and reference point. Then, that this order quantity may be larger than the risk-neutral one’s if the reference point is less than a negative threshold. In addition, although the effect of random yield leads to an increase in the order quantity, the loss-averse newsvendor may order more than, equal to or less than the classical one, which significantly depends on loss aversion level and reference point. Numerical experiments were conducted to demonstrate our theoretical results.

Keywords: newsvendor problem; random yield; loss aversion; reference dependence (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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