| The sharing economy is developing rapidly and the Internet has expanded from the consumer sector to the production sector.The online ride-hailing service that belongs to the ‘Internet + Shared Transport’ model has emerged at the historic moment.Online ridehailing service has developed rapidly in China and has changed the travel demand.This comfortable and low-cost travel service may lead to the transfer from green modes,and even cause the inducement of travel demand,increases people’s willingness to buy cars.The impact on urban traffic congestion is worth discussing.In this study,from the perspective of urban residents’ travel behaviors,combined with the significant influencing factors,we explored the influence mechanism of online ridehailing on urban traffic,and then provided opinions and references for the government and online ride-hailing company.Specifically,taking Di Di users as the survey object,based on the large sample data obtained from the questionnaire survey,the influencing factors of ride-hailing on the travel behavior were studied.Multiple logistic models were used to analyze the mode choice and the transfer behavior by online ride-hailing service.The association rules and decision trees were used to perform data mining on the inducement of travel demand after the emergence of online ride-hailing service.Random forest was used to study the behavior that urban residents buy and sell cars by online ridehailing service.The study found that:(1)For travel mode transfer behavior: Taxi accounts for the largest proportion(39.50%),followed by rail transit and buses and private car has the lowest,at only 5.87%.People who mainly use shunfengche,use Di Di at peak hours,who are very satisfied with Di Di service,whose main use of Di Di is commuting may transfer from green modes.This shows that during peak hours,for commuting demand,green modes has insufficient capacity and cannot provide a satisfactory service experience.At the same time,users who transfer from green mode often use shunfengche service.Compared with other ridehailing service,shunfengche has a low road resource occupancy rate which helps to alleviate the increase of urban traffic load caused by the transfer behavior during peak hours.(2)For inducement behavior: 11.28% of users’ travel demand are being induced by ridehailing service.The inducement caused by online ride-hailing is mainly non-commuting demand at off-peak hours,the travel frequency is relatively low.Because commuting travel demand at peak hours is rigid high-frequency demand,there is not much room to be attracted by the online ride-hailing.Therefore,the inducement behavior has limited impact on the increase of urban traffic load during the peak hours.At the same time,the ride-hailing mode itself is equivalent to multi-ride sharing.It is more intensive than car,taxi and other online car services,and it also helps overall urban transportation stable.(3)For the willingness to buy or sell a car: About 5.97% of the users will sell cars,and the majority(75.36%)will not.59.73% of Di Di users still plan to buy cars,which is higher than those who will not(40.27%).People who mainly use kuaiche,who are basically satisfied with Di Di service are more likely to buy cars,and their willingness to sell cars is relatively low.People who are not satisfied are also likely to buy a car.Users who use Di Di during peak hours have a strong willingness to buy a car.It can be seen that ride-hailing service,while alleviating the tight supply during peak hours,stimulates users’ demand for car purchase.Users with high willingness to buy a car mainly travel at peak hours which may aggravate peak hours traffic load.Finally,this article proposes feasible strategies and policy suggestions for the online ridehailing company and government based on the factors that affect the travel behavior in order to promote the healthy development of online ride-hailing service in urban transportation. |
PDF Full Text Request