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CVaR准则下考虑过度自信行为的报童模型研究
引用本文:陈克贵,黄敏,王新宇.CVaR准则下考虑过度自信行为的报童模型研究[J].东北大学学报(自然科学版),2020,41(4):475-481.
作者姓名:陈克贵  黄敏  王新宇
作者单位:(1.中国矿业大学 管理学院, 江苏 徐州221116; 2.东北大学 信息科学与工程学院, 辽宁 沈阳110819)
基金项目:国家自然科学基金重点国际合作研究项目(71620107003); 国家自然科学基金资助项目(71325002,71871215,71573252); 教育部人文社会科学研究项目(17YJC630012); 能源矿业经济智库(中国矿业大学文化传承专项项目(2018WHCC01).
摘    要:为研究风险厌恶零售商对随机市场需求的信念有过度自信行为时的订货策略,以CVaR作为风险度量准则,建立了CVaR下过度自信的报童模型.探讨风险厌恶程度和过度自信行为对零售商的最优订货决策及相应条件风险值的影响,分析过度自信零售商和完全理性零售商的信念条件风险值与实际条件风险值.研究结果发现:在一定风险水平下,过度自信导致零售商条件风险值降低且订货量偏离完全理性时的情形.数值算例验证了模型的有效性,为现实中零售商的订货决策提供了理论支持.

关 键 词:报童模型  过度自信  风险厌恶  CVaR准则  最优订货量  
收稿时间:2019-04-02
修稿时间:2019-04-02

Newsvendor Model with Overconfidence Behavior Under CVaR Criterion
CHEN Ke-gui,HUANG Min,WANG Xin-yu.Newsvendor Model with Overconfidence Behavior Under CVaR Criterion[J].Journal of Northeastern University(Natural Science),2020,41(4):475-481.
Authors:CHEN Ke-gui  HUANG Min  WANG Xin-yu
Institution:1.School of Management, China University of Mining and Technology, Xuzhou 221116, China; 2 School of Information Science & Engineering, Northeastern University, Shenyang 110819, China.
Abstract:In order to study the ordering strategy of risk-aversion retailers when they have overconfident behaviors in their beliefs in random market demand, CVaR was used as a risk measurement criterion, and an overconfident newsvendor model under CVaR was established. The effect of risk-aversion and overconfidence on retailer’s optimal ordering decision and corresponding conditional risk value was discussed. And the belief condition risk value and actual condition risk value of over confident retailers and fully rational retailers were analyzed. The results showed that overconfidence causes retailer to reduce the risk value of the condition and the order quantity deviates from full rational. Numerical examples verified the validity of the model and provided theoretical support for retailers’ ordering decisions in reality.
Keywords:newsvendor model  overconfidence  risk-aversion  conditional value at risk(CVaR)criterion  optimal order quantity  
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