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作 者:张光远[1,2] 庄河 丁小东[1,3] 黄修莉[1] 王瑶[3] ZHANG Guang-yuan ZHUANG He DING Xiao-dong HUANG Xiu-li WANG Yao(School of Transportation & Logistics, Southwest Jiaotong University, Chengdu Sichuan 610031, China Nation and Region Combined Engineering Lab of Intelligentizing Integrated Transportation, Chengdu Sichuan 610031, China Transport and Economic Research Institute, China Academy of Railway Sciences, Beijing 100081, China)
机构地区:[1]西南交通大学交通运输与物流学院,四川成都610031 [2]西南交通大学综合交通运输智能化国家地方联合工程实验室,四川成都610031 [3]中国铁道科学研究院运输及经济研究所,北京100081
出 处:《公路交通科技》2017年第2期149-158,共10页Journal of Highway and Transportation Research and Development
基 金:中央高校基本科研业务费专项资金项目(26816WTD23);综合交通运输智能化国家地方联合工程实验室团队建设项目(2682016ZT09);中国铁路总公司科技研究开发计划项目(2015X006-C)
摘 要:为了探究决策者的感知偏差对实际订购行为的影响,在经典报童模型基础上,引进缺货规避、损失规避有限理性因子,构建了完全缺货惩罚和部分缺货惩罚策略下损失规避型报童的库存决策模型,采用仿真试验的方法对模型进行了验证。试验结果表明:当决策者受缺货规避偏差影响时,其实际订购量大于报童模型最优解,而当决策者受损失规避偏差影响时,其实际订购量小于报童模型最优解;当决策者受缺货规避偏差和损失规避偏差的双重影响时,其订购行为能够解释报童决策偏差现象。报童决策偏差现象揭示了库存管理实践中考虑决策者的有限理性因子,有利于缩小理论模型与管理实践之间的差距,提高库存管理效率。In order to explore the influence of cognitive preference of decision maker on his actual order behavior, considering fully-stockout-punishment and partial-stockout-punishment strategies, limited rationality factor of stockout avoidance and loss avoidance based on the classical newsvendor model are introduced to establish an inventory decision model,and the model is verify by simulation experiment. The experiment result shows that( 1) the actual order quantity( AOQ) is larger than newsvendor model optimal solution( NMOS) when decision makers are affected by stockout avoidance bias,while AOQ is smaller than NMOS when decision makers are affected by loss avoidance bias;( 2) the order behavior could explain the newsvendor decision bias when decision makers are affected by both stockout avoidance and loss avoidance biases. Newsvendor decision bias indicates that considering decision maker' s limited rationality factor in inventory management practice is conducive to narrow the gap between the theoretical model and management practice,and to improve the efficiency of inventory management.
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