Retailer’s Returns Policies Research Based On The Customers Decision-Making Behavior Of Returns

Compared with the traditional business system, e-commerce, which is relied on Internet, has many advantages and attracts more and more customers to shopping online. However, while the e-commerce is booming in our country and the customer’s requirements on product are in a rapidly rising stage, the phenomenon of customer returns is becoming common. And some data indicate that there are a large number of goods returns which are due to the customer’s own reason. Based on the above background, this paper concludes two kinds of customer behavior that exists in the market. One is that customers who purchase a mismatch product still choose to hold it, another is fraudulent returns behavior. Considering the realistic existence of these two kinds of customer behavior, in this paper, we use modeling analysis to study the retailer’s returns strategy based on the Theory of Consumer Behavior and the Theory of Expected Utility. The results of Arena software analysis showed that the partial refund policy has more advantages than the full refund policy for seller. To illustrate this research in detail, the main contents of this paper are as follows:First of all, this paper sums up the current research way in this field after reviewing the related literature of no-reason returns. Then, this paper expounds the concept of the non-defective product and the fraudulent returns in order to lay a theoretical foundation of next discussion.Secondly, aiming at studying of the strategy of seller for the first kind of customer returns behavior, this paper used the method of customers expected utility to reflect the market demand by analyzing the function of customer purchasing and returns decision, then we proposed the optimal product pricing and the optimal restocking fee with building the retailers expected profit function.At last, this paper talks about the retailers’ return policy in fraudulent returns case. By building the retailers profit function and introducing the simulation with Arena software, we suggested that increasing of failure ratio of goods returning with deceptive intention may cause reducing of the occurrence frequency of the fraudulent returns. We also find that the returns policy with fewer limitations will attract more consumers to buy the product. However, it will induce a large number of fraudulent returns which may not be positive to total profits of retailers.