Research On Differential Pricing Based On Space-time Demand Characteristics Of Shared Bikes

With the rapid development of the sharing economy,shared bikes have gradually become an important mode of transportation for short distance travel.However,due to the lack of understanding and research on the time and space differences of shared bikes demand,the current shared bikes pricing is not reasonable.So many bicycle companies are difficult to continue to develop.At present,the research on pricing strategy mainly focuses on buses and subways.There is a lack of research on shared bikes,especially on the differential pricing of shared bikes.Based on this,the article uses shared bikes operation data and questionnaire data to analyze the space-time demand characteristics of shared bikes.On this basis,the research proposes a bi-level programming model of differential pricing.The main work of this article includes the following four aspects:(1)This article makes a comprehensive analysis on the pricing status,pricing basis and pricing influencing factors of shared bikes.This article puts forward the necessity of optimizing the pricing strategy on the current situation of shared bikes pricing and analyzes the profit characteristics,pricing principles and ticket system selection of shared bikes on the pricing basis of shared bikes.And this article analyzes the internal factors and external factors that affect the pricing,so as to lay a foundation for the construction of shared bikes pricing model.(2)Based on Mobike operation data and questionnaire survey data,this article analyzes the space-time demand characteristics and pricing intentions of users.First,this article decodes and cleans the original data of Mobike operation to ensure the accuracy of the data.Then this article analyzes the time demand characteristics of shared bikes.Finally,this article uses Arc GIS to make a visual analysis of the space demand characteristics of shared bikes from the macro and median levels.The questionnaire survey data was counted according to three types of questions: users' individual attributes,riding characteristics and pricing intentions.Using these data,this paper analyzes the user composition and riding characteristics in peak and flat peak periods,and investigates the user's acceptance of differential pricing strategies.(3)Considering the space-time demand characteristics of shared bikes,this article puts forward the basic ideas and general assumptions of model construction.On this basis,the research constructs a bi-level programming model of differential pricing based on the space-time demand characteristics of shared bikes.In the upper level planning,the objective is to maximize the profits of shared bikes enterprises,and shared bikes pricing is the decision variable.In the lower level planning,the objective is to minimize the generalized travel cost of residents,and the number of users in each mode of transportation with competition is the decision variable.On the basis of the comparison and analysis of the commonly used solving algorithms of the model,the improved particle swarm optimization(PSO)algorithm is selected to design the algorithm of the bi-level programming model.(4)The surrounding area of Beijing Jiaotong University is selected for case analysis of the model.First,the research area is divided into traffic areas based on the improved k-means++ clustering algorithm.On this basis,the specific riding period and starting and ending points are selected.Then the parameters of the bi-level programming model are set for the specific case reference and particle swarm optimization algorithm is used for case.Finally,this article gives the optimal pricing of shared bikes and verifies the convergence of the model.This paper contains 28 figures,20 tables and 62 references.