Applying a latent class cluster analysis to identify consumer segments of electric vehicle charging styles

Abstract

Electric vehicle market growth makes understanding user charging behaviour essential for policy design and EV adoption facilitation. In this study, we examined the heterogeneity in charging preferences of 994 respondents across Australia, using a latent class cluster model that considers indicators of charging behaviour as outcomes of interest. We used sociodemographic characteristics, travel needs, and EV adoption status as covariates to predict class membership. Our findings identify five segments of consumers with distinct charging style preferences: cost-sensitive planners, cost-sensitive on-demanders, predictability seekers, flexibility seekers, and indifferent late adopters. We provide targeted policies for each segment based on their charging style and profile, aimed at facilitating EV adoption and meeting their charging needs. Our results suggest that two broad categories of action are necessary to facilitate EV adoption and meet charging needs of upcoming EV users: improving EV-related knowledge and providing economical home charging options.