Highlights•We investigate factors influencing choice to use one-way and round-trip carsharing.•We rely on stated preference experiment, to pivot from revealed mode choice.•One-way and round-trip carsharing have different utility and significant attributes.•We explicitly model cost, demographics, fuel type, and environmental conditions.•Carshare competes most against other sheltered modes – car, taxi, bus, subway.

AbstractThis study examines the factors that influence the use of carsharing systems in Beijing, as well as the potential for carsharing systems that integrate electric vehicles. Investigated variables include weather, air quality, price, vehicle attributes and “status” indicators. Additionally, we explore how the impacts of these factors differ when carsharing is utilized for one-way trips as compared with round-trips. The study relies on a pen-and-paper survey (1010 completed survey forms with 2023 reported trips) which uses a stated-preference pivoting design to build hypothetical choice sets around actual trips. The data are used to estimate binomial logit regression models for one-way and round-trip carsharing. Results of the analysis indicate that age, car ownership, shelter mode, the original cost for taxi users, perceived parking availability, cold weather, and relative cost differences are significant for one-way carsharing. For round-trip carsharing, significant factors include car ownership, income, gender, environmental concern, and relative cost differences. The most statistically significant factors to attract carsharing customers are the cost gap (defined as cost of original mode – cost of carshare) for both one-way and round-trip carsharing services, and car ownership, which has a positive significant effect for one-way trips and a negative significant effect for round-trips. This paper contributes to the literature by further examining the determinants that affect the use of carsharing, distinguishing between one-way trips and round-trips, and developing models that can be applied in urban environments like Beijing.