前置仓库存容量与品类优化策略研究OA北大核心CHSSCDCSSCICSTPCD

Under the impact of the internet,the traditional retail industry has gradually transformed into a new retailing format.This transformation is characterized by a closer integration between online and offline channels and is more consumer-centric.The traditional e-commerce mode comprises an"online platform+offline central warehouse distribution",which usually takes 1 to 5 days to deliver a product.With the development of new retail,proactive warehouses,due to their fast response advantage,are playing an increasingly important role in logistics services.However,the capacities of proactive warehouses are relatively small,and only a small volume of goods can be accommodated in these warehouses.Therefore,the capacity level and the assortment are two key considerations in proactive warehouse management.In this paper,we analyze a retailer's joint capacity and assortment decisions for a proactive warehouse in two different modes(with or without a delivery from a central warehouse). In the first part,the product order quantity and capacity decisions for the proactive warehouse of the nondelivery mode are studied.We solve the problem via backward induction.First,given the capacity,we solve the profit model of the proactive warehouse to obtain the responsive order quantity decisions for two products(high-value product and low-value product).After obtaining the responsive order quantities,we further solve the optimal capacity.The results show that although the total demand is deterministic,the optimal capacity of the proactive warehouse may be higher,equal to or lower than the total demand,depending on the purchasing costs of both products and the unit capacity cost of the proactive warehouse.In addition,the proactive warehouse may only order high-value products or both high-value and low-value products.Specifically,when the purchasing costs of the two products and the unit capacity cost of the proactive warehouse are low,the optimal order quantities of the two products are"partially decoupled",i.e.,the optimal order quantities of the two products do not affect each other.Therefore,even if there is substitutability between the two products,the optimal order quantity for one product remains at a relatively high level when the order quantity of the other product is high. In the second part,the product order quantity and capacity decisions for the proactive warehouse of the delivery mode are examined.We use the same logic as in the nondelivery mode to solve for the optimal product order quantity and capacity of the proactive warehouse.The results indicate that the optimal capacity of the proactive warehouse may also be higher,equal or lower than the total demand.In addition,different from the nondelivery mode,the equilibrium results of ordering only high-value products,only low-value products,and both products in the proactive warehouse can occur.This is because in the nondelivery mode,the retailer orders only high-value product due to its higher profit margin,while in the delivery mode,the retailer's decision is based not only on the profit margin of the product but also on the revenue of the central warehouse when it meets the demand. Next,we compare and analyze the nondelivery and delivery modes.We find that the total inventory capacity of both modes decreases from above to below the total market demand as the unit capacity cost of the proactive warehouse increases.In some cases,the product category of the proactive warehouse changes from two products to only high-value products in the nondelivery mode and from two products to only high-value or only low-value products in the delivery mode.The optimal capacity of the nondelivery mode is higher than that of the delivery mode when both products are ordered.In addition,the optimal order quantities of both products are higher in the nondelivery mode when the optimal capacity is higher than the total market demand.The order quantity is higher for high-value products and lower for low-value products in the nondelivery mode when the optimal inventory capacity is equal to the total market demand. Finally,we conduct a numerical analysis of the results in the nondelivery and delivery modes.The results show that when the substitutability of products is low,for a given capacity,the order quantity of high-value product is higher in the nondelivery mode than in the delivery mode,while the order quantity of low-value product is lower,and vice versa.In addition,when the marginal profit of the low-value product is low,the optimal capacity in the delivery mode is always lower than that in the nondelivery mode.Interestingly,the optimal order quantity of the high-value product in delivery mode is always lower,while the optimal order quantity of the low-value product could be higher or lower in the delivery mode.When the marginal profit of the low-value product is high,the optimal capacity in the delivery mode is higher than that in the nondelivery mode under certain conditions because the retailers of the two modes order different products.Specifically,the retailer orders only more low-value product in the delivery mode,while he or she orders only a relatively small amount of high-value product in the nondelivery mode.In summary,in the context of new retail,online and offline channels are more closely integrated,and consumers become more concerned about services.Proactive warehouses are favored by an increasing number of e-commerce firms,especially those in the fresh food industry,due to the small-batch and high-frequency delivery.Therefore,it is necessary for retailers to make rational decisions on the capacity of proactive warehouses and to perform assortment optimization.In this paper,we study the capacity and assortment optimization of a proactive warehouse with or without a central warehouse delivery and solve the problem by using the newsboy model to analyze the optimal capacity and optimal order quantity of the proactive warehouse under these two modes,which provides theoretical decision support for managers to optimize the capacity levels and assortments of proactive warehouses.