Understanding members' carsharing (activity) persistency by using econometric model

This article reports on a research study undertaken to better understand the behavior of carsharing users, particularly their persistence in using this transportation modality. The authors model the probability of the users being active (using the carsharing system) as well as their monthly frequency of use, using real transaction datasets (40 months of operation of a Montreal, Canada carsharing company). For every member, a two-stage approach microsimulates the probability of being active in any month using a binary probit model and given that a particular member is active during a month, the probability of that member using the service multiple times using a random utility-based model. Results show that the activity persistence of members is positively linked to previous behaviors for up to 4 months, and that the influence of previous months weakens over time. The study also showed that some attributes of the traveler (gender, age, and language spoken at home) have an impact on travel behaviors. The authors conclude that paying more attention to the day-to-day behavior of clients will improve understanding of the carsharing system and contribute to a better assessment of the true market and impacts of carsharing in an urban area.