需求预测信息共享中基于信任的价格折扣模型

发布时间：2018-05-22 07:18

本文选题：需求预测 + 信息共享　；参考：《计算机集成制造系统》2017年12期

【摘要】：为解决供应链上下游企业间需求预测信息的有效共享问题,针对由一个制造商和一个零售商组成的供应链,利用斯坦科尔伯格博弈方法分别建立了单周期和多周期环境下基于信任和价格折扣的协调模型。模型假定在销售季节前零售商对市场需求进行预测并汇报给制造商,制造商据此确定自己的产能。当销售季节来临后,零售商下达正式的订单。制造商通过比较需求均值预测值和真实值的差异确定对零售商的信任度,进而确定给零售商的批发价格折扣。分别给出单周期与多周期模型的求解算法,并结合数值算例进行分析。研究结果表明:当折扣比例上限确定时,零售商存在最佳的需求预测汇报值;若价格折扣比例合适,供应链成员可以达到优于共享真实预测信息的效果。
[Abstract]:In order to solve the problem of effective sharing of demand forecasting information between upstream and downstream enterprises in the supply chain, a supply chain consisting of a manufacturer and a retailer, By using the Steinkelberg game method, the coordination models based on trust and price discount are established in single-cycle and multi-period environments, respectively. The model assumes that retailers forecast and report market demand to manufacturers before the sales season, according to which manufacturers determine their capacity. When the sales season comes, retailers place official orders. The manufacturer determines the trust degree to the retailer by comparing the difference between the forecast value of the average demand and the real value, and then determines the wholesale price discount to the retailer. The algorithms for solving single-period and multi-period models are presented, and the numerical examples are used to analyze them. The results show that when the upper limit of discount ratio is determined, retailers have the best demand forecast reporting value, and if the price discount ratio is appropriate, supply chain members can achieve better results than sharing real forecast information.
【作者单位】：青岛大学商学院;上海交通大学国际与公共事务学院;
【基金】：国家自然科学基金资助项目(71501128,71202143,71202142) 山东省自然科学基金资助项目(ZR2015GM001) 上海交通大学文理交叉基金资助项目(15JCZY05) 青岛市博士后应用研究资助项目(2015173)~~
【分类号】：F274

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