Determinants of Passenger Satisfaction with Ride-Hailing Services: Case Study in Nanjing, China

• Published in: Journal of urban planning and development Vol. 149; no. 2
• Main Authors: Wang, Ting, Zhang, Yong, Li, Yu, Li, Meiye, Lu, Wenbo
• Format: Journal Article
• Language: English
• Published: New York American Society of Civil Engineers 01-06-2023
• Subjects: Car sharing; Case Studies; Case Study; Customer services; Indicators; Logit models; Passenger satisfaction; Passengers; Sensitivity; Sustainability; Sustainable development; Transportation networks; Urban development; Urban planning; China
• ISSN: 0733-9488; 1943-5444
• DOI: 10.1061/JUPDDM.UPENG-3960

Abstract
Ride-hailing services have become essential traffic services for the sustainability of urban mobility. However, owing to extensive development, many challenges face ride-hailing services, such as financial sustainability and passenger trust, especially in China. Passenger satisfaction plays an important role in passenger loyalty and passenger trust. In this study, a passenger questionnaire-based survey was conducted in Nanjing, China. The questioned 1,721 passengers are divided into three categories, namely infrequent passengers, moderately frequent passengers, and frequent passengers. Three ordered logit models were developed for different passengers, to explore factors influencing passengers’ satisfaction with ride-hailing services. Further, how the significant factors affect passengers’ overall satisfaction was investigated. The results show the service indicators for infrequent passengers are the most significant. Infrequent passengers are more concerned about waiting time, and have the highest sensitivity to the safety level of ride-hailing services. Moderately frequent passengers are more sensitive to whether drivers charge according to regulations and actively inform passengers. There are four common significant service indicators for three types of passengers. Among these common indicators, infrequent passengers have the highest sensitivity to all the common indicators except the service quality of the customer service department, and frequent passengers have the lowest sensitivity to all of the common indicators. All types of passenger are most sensitive to price. Finally, some suggestions are given for transportation network companies and transport agencies. The obtained conclusions and given suggestions are helpful for urban planners to do better in promoting the sustainable development of ride-hailing services. The analysis method and model presented here can provide a useful reference for other cities.