Carsharing Versus Bikesharing: Comparing Mobility Behaviors. Issue 1 (2017)

• Record Type: Journal Article
• Authors: Wielinski, Grzegorz; Trépanier, Martin; Morency, Catherine
• Is Part Of: Transportation research record. Volume 2650:Issue 1(2017)
• Page Start: 112
• Page End: 122
• Publication Date: 2017
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.3141/2650-13
• Languages: English
• ISSNs: 0361-1981

Abstract

Shared mobility services such as carsharing and bikesharing have gained significant traction in recent years. The services offer efficiency and flexibility to their members while providing benefits to society. In fall 2013, two origin–destination web surveys were carried out on carsharing and bikesharing members in Montreal, Quebec, Canada. These data were used to analyze the typical travel behaviors of members of one or both services. Service provider data were supplied to complement the analyses. The study controlled for factors such as age, gender, home location, and intensity of use of the service. Person and household characteristics showed that bikesharing users differed by being younger, more often male, and more connected (smartphones), and having a higher income. Carsharing users possessed more transit passes, had driving licenses in a higher proportion, and belonged to households with more children and fewer cars. Differences were also found when the intensity of the use of the service was accounted for. On travel behaviors, the study analyzed mode share when the bikesharing service was in operation and when the service ceased operations. On the former, both groups had high shares of public transit and walking, but bikesharing users were more car (driver)-oriented and carsharing members had a higher use of bikes. On the latter, carsharing users increased their use of walking, and bikesharing users increased their use of cars (driver). Finally, the study used a multinomial logit model to evaluate the performance of several variables on the odds of being a carsharing-only member, a bikesharing-only member, or a member of both services.