Inventory Model Based On Consumer Online Search

Inventory management has always been one of the most important issues for academic researchers and supply chain practitioners.The rapid development of Internet has provided useful information for both consumers and retailers.It has changed the way business operates.The constanly changing market poses new problems and challenges to traditional inventory management.Consumer online search behavior provides retailers with market advance demand information in a completely different way.However,the existing related literature mainly focuses on inventory management with perfect advance demand information,which is not consistent with imperfect advance demand information generated by search data.Therefore,we still need to explore new methods to guide enterprises to carry out scientific inventory management.Based on this,this paper focuses on the behavior characteristics of consumers and retailers in the online search environment,and uses the research method of combining mathematical model with empirical analysis to build an inventory model based on consumer online search.This paper is aimed to provide a theoretical basis for scientific inventory management and help enterprises create value by using search data in competitive environment.It also provides a feasible method for enterprise managers to identify statistical consumer online search indicators in mass data and to drive decision-making by data.Specifically,the research work and conclusions of this paper mainly include the following aspects:(1)This paper makes a systematic classification and summary of the domestic and foreign research on consumer information search behavior and inventory management with advance demand information.(2)Describe in detail the search behavior of consumers and the inventory decision behavior of retailers in the online search environment,then make theoretical abstraction,construct the inventory model based on consumer online search,and analyze the ordering strategy.The results show that the optimal ordering strategy under the online search environment is to adopt the order-up-to inventory management strategy,and the order-up-to point increases with the increase of the total number of potential consumers.If the total number of potential consumers at the beginning of each period is the same,the order-up-to point of the last period in the planning horizon is the upper limit of all periods.(3)Quantitative measurement and analysis of information value generated by search data are carried out by using two indicators: the revenue loss ratio and the difference of inventory cost that take into account and don't take into account advance demand information.The results show that the inventory holding cost and shortage cost of retailers can be significantly reduced by 5%-10% when the advence demand information generated form search data is taken into account in the inventory model.And the revenue loss ratio increases with the increase of demand conversion rate,decreases with the increase of effective lead time,and increases with the increase of variation coefficient of potential consumers.(4)Based on the digital traces left by consumers in the decision-making process,this paper uses genaral search index and specfic search index to measure consumer online search behaivior,and then explores the relationship between consumer online search index and the demand conversation rate proposed in the model.On this basis,the relationship between the consumer online search index and the retailer's inventory strategy is futher analyzed with the conclusions of Chapter III and Chapter IV.The results show that consumer online search can indeed provide useful information for retailers to predict demand conversion rate.Each search has its own stochastic impact and the effects of these searches accumulate.