This paper aims to explore the potential of car-sharing in reducing car ownership and what are the impact factors. Based on the data of Hangzhou “Fun Car-sharing” system, a discrete choice model was established to study the willingness to postpone car purchase with participation in car-sharing. Compared with previous studies, this study included the variables involved in the questionnaire and those related to the usage characteristics extracted from rental data and GPS data. The questionnaire data indicate that about 50% of respondents will postpone car purchase by participating in car-sharing. The discrete choice model indicates that car-sharing in China can play a role in delaying car purchase. The results further suggest that respondents who use car-sharing more frequently, travel to work by car, or have an activity anchor in their trip are more likely to postpone car purchase. Moreover, respondents whose most common travel purpose of car-sharing is work-related or car purchase plan is definite are less likely to postpone car purchase after participating in car-sharing. The insights gained in this study can help cities and car-sharing operators to formulate relevant policies and regulation that optimally integrate car-sharing services into the overall urban transport systems.

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Carsharing as a means to provide individuals with access to automobiles to complete a personal trip has grown significantly in recent years in China. However, there are few case studies based on operational data to show the role carsharing systems play in citizens' daily trips. In this study, vehicle GPS data of a round-trip carsharing system in Hangzhou, China was used to describe the trip chain characteristics of users. For clearer delineation of carshare usage, the car use time length of all observations chosen in the study was within 24 h or less. Through data preprocessing, a large pool (26,085) of valid behavior samples was obtained, and several trip chaining attributes were selected to describe the characteristics. The pool of observations was then classified into five clusters, with each cluster having significant differences in one or two trip chain characteristics. The cluster results reflected that different use patterns exist. By a comparative analysis with trip survey data in Hangzhou, differences in trip chain characteristics exist between carsharing and private cars, but in some cases, shared vehicles can be a substitute for private cars to satisfy motorized travel. The proposed method could facilitate companies in formulating a flexible pricing strategy and determining target customers. In addition, traffic administration agencies could have a deeper understanding of the position and function of various carsharing modes in an urban transportation system.

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