Modeling the demand for electric mobility in the Canadian rental vehicle market. (December 2018)

• Record Type: Journal Article
• Authors: Dimatulac, Terence; Maoh, Hanna; Khan, Shakil; Ferguson, Mark
• Is Part Of: Transportation research. Volume 65(2018)
• Page Start: 138
• Page End: 150
• Publication Date: 2018-12
• Subjects: Canada -- Rental vehicle -- Electric vehicles -- Latent class model -- Stated preference; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2018.08.002
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: Consumers' demand behavior for renting electric vehicles (EVs) is understudied. A nationwide Stated Preference survey is conducted to assess consumers' preferences towards renting EVs. A latent class model identified four distinct population segments in the collected data. Vehicle driving range and battery recharging time are key to the adoption of EVs in the rental sector. Abstract: In recent years, numerous studies have been conducted to evaluate the demand for acquiring electric vehicles (EVs) by household with little attention given to the commercial fleet sector. Within the latter, rental vehicles account for the majority of fleets in Canada. Eventually, the acquisition of rental vehicles by their respective companies is driven by consumers' demand for these vehicles in the market. This research provides a pioneering effort to evaluate Canadian consumers' preferences towards renting EVs. A nationwide stated preference (SP) survey was conducted to collect information from over 1000 respondents. Each respondent was presented with six choice scenarios, and each scenario featured the following vehicle powertrains: internal combustion engine vehicle (ICEV), hybrid electric vehicle (HEV), plug-in hybrid electric vehicle (PHEV) and battery electric vehicle (BEV). The collected SP responses, along with socio-demographic and attitudinal characteristics of the respondents, were analyzed using a latent class discrete choice model to identify the potential segments with unique features present in the sample population. The model identified the following four distinct latent classes: ICEV-oriented (22%), EV-curious (34%), Cost-sensitive (24%), and EV-oriented (20%). Based on the empirical analysis, the potential for renting electric vehicles among the EV-curious and the EV-oriented classes could increase with improvements in vehicle driving range and battery recharging time. Further, provision of monetary incentives (e.g., free vehicle upgrades, rental discounts and no rental taxes) could also increase the probability of renting HEVs by the Cost-sensitive consumers.