Resilience Influence Of On-Demand Ride Services System Under COVID-19

With the development of digital and information technology,the ride-hailing mode,which aims to provide personalized real-time travel service arised,relying on the mobile Internet and big data technology,and taking the online taxi-hailing platform as the carrier,achieved point-to-point interconnection and efficient matching between travelers and vehicles.However,the global public health event of the COVID-19 epidemic in 2020 broke the stable state of the oline ride-hailing system.This thesis focuses on the influence factors of COVID-19 epidemic on the resilience of on-demand ride services system.According to the influence degree of the factors,this thesis puts forward the optimization strategy of improving the system resilience,in order to enhance the system’s resistance,adaptability and resilience.First of all,this thesis lists the general table of the factors affecting the resilience of on-demand ride services through literature review and expert interviews.Secondly,the online travel order data and online questionnaire survey data were collected and analyzed in Ningbo,considering the availability of various factors,reducing the complexity of modeling and improving the prediction accuracy of the model,to abstract the key factors that affect the resilience of the system under the background of the pandemic,and explore the interaction among the factors.Thirdly,the hierarchical structure diagram of the influencing factors of toughness is constructed based on the Interpretation Structure Model(ISM),and the toughness index of each factor is quantitatively analyzed by Bayesian analysis,focusing on the transmission chain of key risks.Fourth,measure the goodness of fitting of the statistical model,and verify the results based on the Akaike Information Criterion(AIC)and Bayesian Information Criterion(BIC),to get the best fit.The model with the number of travel orders of net appointment as the system toughness index is the most suitable to the actual situation of network travel system toughness.Fifth,combined with the evaluation model of toughness factors,aiming at the system toughness decision-making factors and variable factors,the optimal management strategy of network travel system toughness under the pandemic background is put forward from the three aspects of system toughness resistance,adaptability and recoverability.Finally,the author uses simulation,questionnaire survey and other methods to verify that the optimization of toughness factors has a positive effect on the overall system toughness.This paper puts forward a resilient and optimal management strategy for the ondemand ride services system under the background of COVID-19 ’s epidemic.On the one hand,it provides decision can be used as reference for transportation management department,strengthen the safety management level of the on-demand ride services system.On the other hand,it will help improve the stable operation and management theory of the ride-hailing industry,and provide reference for the future research on the development path.