Joint Optimization Of Inventory And Ordering Considering Non-defective Returns In Online Retailing

A distinguishing feature of online retailing that differs from traditional storefront operations is the existence of a large number of non-defective returns resulting from non-quality reasons.Due to the limitations of online shopping in the release of commodity information,the inaccuracy or deliberate beautification of the information released by the retailer,and the influence of the individual differences in the process of accepting the commodity information,customers often get dissatisfied after receiving the physical goods and choose to return.A large number of returns increase the complexity of inventory management,which is an important issue in inventory management research in online shopping environment.Since non-defective returns can be resold during the sales period,it is necessary to consider this issue when developing an inventory strategy before the start of the sales period.At the same time,the amount of returns is significantly affected by the price,so while optimizing inventory,it is necessary to consider the impact of the price.This paper addresses the issue of pricing and inventory joint optimization with non-defective return resales,from the perspective of price impact on demand and returns,gradually relaxes the assumptions of the relationship between return volume and price,and uses analytical analysis combined with simulation modeling to conduct the research.The main research contents and conclusions are as follows:(1)For the single-cycle problem of return sales in the same period,the inventory and pricing joint optimization models with fixed return rate and return rate changing with price are established respectively,and the existence and uniqueness of the optimal solutions are proved for the deterministic problems.The expected profit models for stochastic problems are established and the algorithms for solving optimal price and optimal order quantity are designed.The theoretical and numerical example analyses show that the optimal pricing is low and the maximum profit is higher than those when the re-sale of the return is not considered,and the "win-win" between the customer and the retailer can be realized.(2)From the perspective of perceived value and perceived difference,the customer’s online purchase and return decision are analyzed.The analysis shows that this expression is consistent with the conclusions in the existing empirical research that the higher the commodity price is,the higher the return rate is,and it can better explain the reason for the high return rate after the price reduction promotion period.Based on this statement of return rate,the expected profit models in the daily sales period and promotion period are established respectively,the analytical solution of the optimal ordering strategy is derived,and the calculation methods of the optimal daily selling price,the optimal promotional period price discount,the maximum expected profit during the daily sales period and the promotion period are given.Through numerical examples,it is verified the law that the maximum profit changes with the degree of information beautification when the perceived value and the perceived difference are subject to a more general distribution form and the number of customers is random.The effect of the correlation between the two on the effectiveness of beautification strategies is also studied.(3)For the continuous inventory problem of the return caused by the customer’s perceived difference,and can be re-sold for an unlimited number of times,a hybrid modeling method based on Agent-based simulation and system dynamics simulation is adopted to establish profit models for a fixed price strategy and a promotional period price discount strategy to simulate and optimize inventory and ordering strategies.The results show that with the two-stage pricing strategy of firstly setting a higher selling price.then reducing the price to expand the sales volume,and a continuous inventory(r,Q)strategy with partial consideration of the amount of in-transit return,the optimization goal of rapid cost recovery and profit maximization can be achieved at the same time.