本文在双渠道VMI供应链中,假设制造商和零售商分别处于领导者和追随者的地位,考虑了制造商通过联合促销协调供应链上下游的策略以及双渠道需求之间的搭便车效应,以此为背景建立了制造商和零售商之间的Stackelberg博弈模型,并通过拉格朗日乘数法求解出了制造商的最优发货策略和零售商的最优定价与促销策略。研究发现制造商开辟网上渠道直销产品后,零售商缺货时间比例增大。进一步研究发现,制造商承担促销成本的比例,双渠道之间的搭便车效应对供应链成员的决策和利润有显著影响。另外,双渠道的需求越不稳定,则制造商开辟网上销售渠道后获利越高,同时零售商的利润越低。最后,通过算例验证了模型的有效性并对模型中主要参数进行了灵敏度分析。
With the development of E-commerce, more and more manufactures have established a online distribution channel while keeping traditional retail channel, thus having dual channel to distribute products. Online distribution channel helps manufactures widen the market scope and decrease the operation cost. But it also hurts the retailers profit, thus being subject to retailers' resistances and lead to channel conflict. The appearance of VMI pattern inspires research into competing and coordination strategies for dual channel under VMI supply chain. However previous researches didn't focus on these supply chain. Based on a two-stage VMI supply chain including a manufacturer and multiple retailers, a model of Stackelberg game between a manufacturer and retailers is developed in this paper, considering cooperative promotion in which supply chain can be coordinated and online distribution channel established by manufacturer. The decision variables of manufacture include the quantity of retailers' order, the cycle of retailers' order and price of product which is sold via online channel. Retailers need to determine price of product sold via traditional retailer channel and promotion quantity. It is found that fraction of backlogging rate for retailers become bigger compared with a supply chain without online distribution channel. Furthermore, the increase of cooperative promotion ratio and the fade of free riding' effect leads to higher quantity of promotion; the increase of demand transformation between dual channel leads to higher profit of manufacturer and lower profit of retailers and the whole supply chain. Finally, a numerical example is given to illustrate the theoretical results of the proposed model and conduct sensitivity analysis on parameters of the proposed model.
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