Characterizing usage patterns and trip purposes of carsharing Systems: A multi-city analysis in China

• Employ Bayes’ rules to infer carsharing travel purposes of 4.8 million trips across 58 cities. • Investigates distinctive characteristics of carsharing usage patterns in different cities. • Examine how urban and system characteristics influence usage under various trip purposes. • Support policy formulation for local governments and operational strategies for carsharing companies. Carsharing provides a convenient travel option and has attracted increasing attention in Chinese market in recent years. This study conducted an analysis of carsharing travel patterns and purposes across multiple Chinese cities. We collected over 4.8 million trips from 58 cities, employed Bayes’ rules to infer users’ trip purposes and analyzed their travel patterns within a comparative analytic framework. The analysis explores variations in carsharing usage and trip purposes across cities and examines how urban characteristics influence various trip purposes. The results reveal a strong preference for leisure-oriented travels using carsharing services. There are more work-related trips during daytime and leisure activities in the evenings on weekdays and predominantly leisure activities on weekends. Additionally, there is considerable variability in the distribution of trip purposes across cities. The megacity demonstrates a more balanced usage pattern, whereas the Super-Large City shows a higher demand for commuting trips. In Large City I and Large City II, carsharing is primarily used for leisure and recreational trips. Some carsharing system characteristics, including the number of carsharing parking spaces and shared vehicles, are associated positively with carsharing utilization for different trip purposes, while other factors, like population and road densities, show varying impacts. This study offers a systematic exploration of carsharing services in China and contributes to improving the efficiency of carsharing services in diverse urban contexts.