Identifying and characterizing potential electric vehicle adopters in Canada: A two-stage modelling approach

Mohamed, M.; Higgins, C.; Ferguson, M.; Kanaroglou, P., 2016, in Transport Policy

doi:10.1016/j.tranpol.2016.07.006
Location Canada
Population General
Sample size 3505
Factor analysis type confirmatory factor analysis, nan rotation
Stepwise regression no
Removal of insignificant variables no
Reviewed by LCM

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. © 2016 Elsevier Ltd

Factors

Models

Source variable Target variable Effect p-value Effect type
Environmental concern (ENC) Attitude (ATT) 0.543 0.0 direct_effect
Environmental concern (ENC) Subjective norm (SUN) 0.544 0.0 direct_effect
Environmental concern (ENC) Perceived behavioural control (PBC) 0.508 0.0 direct_effect
Environmental concern (ENC) Personal moral norm (PMN) 0.813 0.0 direct_effect
Attitude (ATT) Behavioural intention (BIN) 0.397 0.0 direct_effect
Subjective norm (SUN) Behavioural intention (BIN) 0.078 0.0 direct_effect
Perceived behavioural control (PBC) Behavioural intention (BIN) 0.479 0.0 direct_effect
Personal moral norm (PMN) Behavioural intention (BIN) 0.124 0.0 direct_effect
Additional vehicle Behavioural intention (BIN) 0.086 0.001 direct_effect
Education Behavioural intention (BIN) 0.02 0.004 direct_effect
Age Behavioural intention (BIN) -0.037 0.0 direct_effect
Employment Behavioural intention (BIN) 0.032 0.004 direct_effect
Garage Behavioural intention (BIN) 0.036 0.001 direct_effect
Gender Behavioural intention (BIN) 0.01 0.617 direct_effect
Income Behavioural intention (BIN) -0.006 0.391 direct_effect
Dwelling type Behavioural intention (BIN) 0.004 0.689 direct_effect
Ann_km Behavioural intention (BIN) 0.0 1.0 direct_effect
HH size Behavioural intention (BIN) 0.017 0.034 direct_effect

The Attitudes and Travel Database is produced with support from the Center for Teaching Old Models New Tricks at Arizona State University, a University Transportation Center sponsored by the US Department of Transportation through Grant No. 69A3551747116.

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