Carsharing services give users short-term, on-demand access to a fleet of shared vehicles, allowing users to gain the benefits of vehicle ownership without having to take on the additional costs and responsibilities. Since the launch of carsharing services in North America in 1998, three models have emerged: (1) roundtrip carsharing (users pick up and drop off vehicles at the same location); 2) one-way carsharing (users can pick up and drop off vehicles at different designated locations); and (3) peer-to-peer (P2P) carsharing (operators facilitate short-term rentals between vehicle owners or hosts and guests or drivers) (Shaheen et al., 2019).
As of October 2018, the global carsharing market was active in 47 countries across six continents, with approximately 32 million members sharing over 198,000 vehicles. The largest carsharing region was Asia with 22.7 million members, accounting for almost three-quarters of the market, followed by Europe, accounting for 21% of carsharing members and 31% of vehicle fleets. From 2016 to 2018, the number of carsharing members worldwide increased by 238%, while the carsharing vehicle fleet grew by 103% (Shaheen & Cohen, 2020).
Carsharing shifts the conventional cost structure of driving from fixed costs (e.g., monthly car payments and insurance payments) to variable costs (e.g., paying by time or distance of use). Carsharing also increases the efficiency of vehicle use by employing a fleet of shared vehicles rather than personally owned vehicles, which are used on average only 4.6% of the time (Fraiberger & Sundararajan, 2017). As a result, carsharing has been shown to impact the travel behavior of users, including transportation mode choice and vehicle ownership. These travel behavior impacts have broader implications on transpor-tation sustainability through reducing vehicle miles traveled (VMT) and shifting users to other, more sustainable modes (e.g., public transit or active transportation, such as cycling). While numerous studies have investigated the impact of roundtrip carsharing on travel behavior, comparing their findings can be difficult due to differences in data collec-tion, methodologies, and analysis models, as well as limited survey sample sizes and data aggregation (Cohen & Shaheen, 2016).