Identifying and characterizing potential electric vehicle adopters in Canada: A two-stage modelling approach. (November 2016) - Mohamed, Moataz; Higgins, Chris; Ferguson, Mark; Kanaroglou, Pavlos
Abstract: This article presents a two-stage structural equation modelling and segmentation process to identify likely electric vehicle adopters in Canada. Using a sample of 3505 households who have expressed an interest in the future purchase of an economy car, the paper operationalizes an extended version of the Theory of Planned Behaviour in a structural equation model to quantify the impacts of personal beliefs on individual adoption intention towards electric vehicles. Model results show that attitude, perceived behavioural control, and norms (moral and subjective) have significant direct impacts on behavioural intention, while a household's concern for the environment has an indirect impact. Age, level of employment, and employment status are identified, among other variables, to significantly influence the adoption intention. Collectively, findings indicate that beliefs vary across socioeconomic and demographic characteristics. To best characterize the most likely group of early adopters, we then conduct a Two-Step cluster analysis on households with a high demonstrated intention to adopt EVs. This results in three distinct socio-economic and demographic segments: Typical Early Adopters, Emerging Early Adopters, and Interested Retirees. Each have their own unique socioeconomic and demographic profile. Insights derived from this work can help tailor marketing strategies that are important for accelerating the adoption of electric vehicles in the future. Highlights: An extended TPB is proposed to identify intentions to adopt EVs. Attitudes, personal norm, social norm, and perceived control matter the most for EVs adoption intention. Environmental concern is important, but not significant determinant of EVs adoption intention. Few socio-economic variables had significant impact on EVs adoption intention. Consumers with high intention to adopt EVs is clustered in three distinct segments.