Research On The Optimal Trade-in Strategy For Retail Platforms Under Agency Sales

With the development and maturity of e-commerce,the agent sales model has been widely used in online retail platforms,and a large number of manufacturers have joined forces to create online venues for customers to enjoy various consumer services through the agent sales model.As a representative service that can effectively improve customer experience and increase customer stickiness,trade-in has also taken this opportunity to enter the network interaction mechanism of agent sales,and is gradually becoming popular in retail platforms such as Tmall and JD.Based on the above background,this article has important theoretical and practical significance to study the issue of autonomous trade-in of retail platforms under the agent sales model.In this article,we not only discuss the optimal trade-in decision for the platform,but also analyze the impact of the platform’s own decisions on other supply chain members(manufacturers,consumers).To solve the above problems,this paper constructs a mathematical model for retail platforms with and without trade-in.Firstly,by comparing the equilibrium profits of retail platforms in both cases,the optimal decision-making range of the platform is solved,and the impact of different factors on the equilibrium results of retail platforms is explained through sensitivity analysis.Secondly,by comparing the equilibrium profits and demands of manufacturers and consumers with or without trade-in,the expected trade-in decision range of other supply chain members is obtained;Thirdly,by comparing the range of trade-in decisions expected by retail platforms,manufacturers,and consumers,this paper explains the decision-making differences among supply chain members,and explains the inherent principles behind the differences;Finally,sensitivity analysis shows the impact of different factors on the equilibrium results of manufacturers and consumers,and further elaborates the stability of the trade-in decision for retail platforms.The research conclusion shows that for retail platforms,the choice of trade-in strategies is influenced by two factors,that is,when and only when the commission rate and unit processing income of old products are in a certain region,the platform is motivated to provide trade-in services;Its trade-in strategy adjustment shows two preferences: in order to maximize its own profits,the platform prefers to provide trade-in services to products with low commission rates and high unit recovery income(such as digital products such as mobile phones and computers).For manufacturers,because manufacturers and retail platforms have a nearly consistent attitude in deciding whether to provide trade-in services,the trade-in service on retail platforms provides opportunities for manufacturers to cooperate,and the platform prefers to cooperate with manufacturers that produce products with lower commission rates and higher unit revenue returns.For consumers,consumers have always been in a relatively weak position in the game of exchanging old for new.Only old customers who hold old products with low commission rates and high unit recovery income are eligible to enjoy the old for new service.Therefore,the old customers in the retail platform who use the old for new service as the market have clarified the characteristics of the old for new product and pointed out the next purchase direction for new customers who expect to participate in the old for new.