需求预测信息共享中基于信任的价格折扣模型

Price discount model based on trust in demand forecast information sharing

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。

To solve the problem of efficient sharing of demand forecast information among upstream and downstream enterprises in the supply chain,Stackelberg game was used to establish coordination models based on trust and pricediscount in single-cycle and multi-cycle environments respectively in a supply chain composed of a manufacturer and a retailer.The models assumed that if the retailer forecasted the market demand and reported it to the manufacturer before the sales season,the manufacturer could determine his own capacity accordingly.When the sales season came,the retailer placed formal orders.The manufacturer determined the trust degree in the retailer by comparing the difference between predicted and real value of demand mean,thereby determining the wholesale price discount to the retailer.The algorithms of single-period and multi-period models were given respectively,and the numerical examples were analyzed.The results showed that when the upper limit of discount ratio was determined the retailer had the optimal reporting value.If the price discount ratio was appropriate,the supply chain members could achieve the performance better than sharing the real forecast information.