The Consumer Behavior And Operation Optimization Under Sharing Economy

With the development of internet and the maturity of payment,sharing economy comes out.Idle resource has been utilized effectively,and the demand of company and consumer are satisfied.On the one hand,resource sharing and operation optimization improve the efficiency of social production and life.On the other hand,new optimization problem arises under sharing economy,such as consumers' choice behavior,optimal pricing,routing planning and so on.The relationship between problems add the complexity of problems This article focuses on consumers' choice behavior,optimal pricing and resource optimization under the background of sharing riding platform and delivery platform,studies and build optimization models and methods to improve the operation efficiency of sharing industries and provide support for development.Based on MNL model,consumer choice model is built under sharing riding in this article.Through research and the parameter estimation of the model,we get the fitted consumer choice model,and do a sensitivity analysis on consumer's behavior.We find,the willing to choose sharing product or service of consumer is influenced strongly by cost of sharing economy,and also related to the experience,service quality and price.Therefore,two extended problems have great impact on the development of sharing economy,such as optimal pricing and resource optimization.The pricing strategy under sharing riding is on the basis of consumer choice model,the routing planning problem of drivers is tackled from the perspective of approximation model.It is found that the pricing decision of platform relates to the order attribution and routing planning.Numerical experiment suggests that,car pooling is more profitable mostly,but not always good for platform.And the saved journey is less and less with the discount growth.Moreover,the cost advantages of sharing economy depends on the scale and distribution of consumer demand,which must be taken consideration while pricing to maximum the profit of platform.On the research of source optimization,the mathematical model for the order assignment and routing problem is established.Two meta-heuristic methods,hierarchical and integrated,are developed for identifying a near-optimal solution for the NP-hard problem.Computational results show that the hierarchical method outperforms the integrated one in terms of the objective value.Comparing to the proximity-based assignment method used in the industry,the hierarchical method can reduce the total traveling distance by over 9 percent.