A Model of Electric Vehicle Adoption and Rank-Based Contributing Factors

Abstract: Electric vehicles (EVs) have broad potential to combat climate change and can provide significant benefits for individual owners. However, EV adoption rates have, thus far, remained relatively low. High up-front costs, limited range, and lack of publicly available charging infrastructure are key issues that have limited the uptake of EVs. As a result, while there is growing interest in understanding individual-level EV adoption decisions, most existing studies have been confined to an examination of adoption intentions rather than actual adoption behaviors. Additionally, there is evidence that individual-level stated intentions do not always align with actual adoption levels.

In the above context, we undertake an individual-level exploration of EV adoption using revealed preference data from a survey undertaken in California. Specifically, we examine the ways that demographics, lifestyle preferences, and perceptions of EVs interact to impact the EV adoption decision. In addition to the binary adoption decision, current EV owners in the California survey were asked to rank the importance of a set of factors that may have influenced their adoption decision, revealing the motivations for EV ownership. We model these outcomes using a Generalized Heterogeneous Data Model (GHDM), a joint modeling framework that accommodates correlation effects between the EV ownership outcome and the ranked reasons for adoption, allowing us to generalize the motivational considerations to potential future adopters. Within this framework, we incorporate four latent constructs representing lifestyle preferences and perceptions of EVs. Two lifestyle-related constructs represent a preference for environmentally conscious behaviors and a view of vehicles as primarily being functional rather than serving to signal social status. The remaining two latent constructs represent perceptions of EVs, in terms of range and charging concerns and relative cost-effectiveness over time compared with internal combustion engine vehicles.

Our results indicate that individuals who exhibit a green lifestyle propensity are more likely to be EV adopters, primarily due to concerns of climate change. Individuals who primarily view vehicles as functional seem less inclined to buy an EV overall, while individuals who view vehicles as status symbols tend to adopt EVs because they are interested in a certain brand or model. Further, those who perceive EVs to be more cost effective and easier to maintain than gas-fueled vehicles, and those with positive perceptions of EV battery technology and range, are more likely to adopt EVs.

The results of this study demonstrate important avenues to promote EV adoption by revealing the different motivations that may influence those with different lifestyle preferences and perceptions of EV technologies. The insights from this model have important implications for the design and deployment of EVs, the development of EV charging infrastructure, and the implementation of information and incentive policies to promote EV adoption.