A Research Of B2C Unreasonable Return Policy Based On Customer Behavior

The B2C unreasonable return policy (B2C-URP) is a welfare which is offered by a retailer to customers, and it permits customers who bought goods to return them to the retailer freely for some refund. Nowadays, there are two inadequate researches: first, from a seller's standpoint only, the majority of literatures ignore customer behavior and consider return as an exogenous variable; second, the few literatures considering customer behavior are limited to customer strategic behavior (namely rational behavior). So based on customer behavior (especially irrational), this paper studies optimal B2C-URP and related operational decision under supply chain environment. The innovations in the dissertation as bellow:(1) Based on customer strategic behavior, the effect of B2C-URP to consumer utility and supply chain performance is analyzed. Also, connected reality, this paper studies the optimal inventory decision when the goods returned can be sold again and the influence of B2C-URP by the return deadline. The results show that: i) the goods re-sale has double-side effect on inventory, and a suitable buyback contract can coordinate the supply chain by eliminating double margin effect; ii) if the distribution of customer return time is independent, the return time-deadline has a positive role on supply chain revenue.(2) Customer quo status (inertia) introduced to B2C-URP, supply chain optimal B2C-URP and coordination is studied when exiting inert customers in the market. The results show the optimal refund, sale price and inventory, and find that the quo status has positive effect on refund, negative effect on sale price and inventory when refund is fixed. In decentralized supply chain, designing the suitable buyback contract and rebate contract can achieve coordination.(3) Customer risk preference introduced to B2C-URP, the influence of B2C-URP by customer different risk preference attribute is discussed in concentrated supply chain. The results show the relation between risk preference coefficient and customer utility, and gain the optimal refund and inventory decision. The B2C-URP is more suitable that the situation of customers seeking for risk, or the greater fluctuation of goods valuation in customer's mind or demand.(4) The simulation model of B2C-URP is established using Anylogic software for the first time. It simulates the customer behavior in the market and the state of goods sale by the method of Agent-based and Event-based respectively. Finally, Individual customer decision and real-time supply chain revenue can be observed.