Factors of electric vehicle adoption: A comparison of conventional and electric car users based on an extended theory of planned behavior

Haustein, Jensen, 2018, in International Journal of Sustainable Transportation

doi:10.1080/15568318.2017.1398790
Location Denmark, Sweden
Population General
Sample size 2467
Factor analysis type principal components, varimax rotation
Stepwise regression no
Removal of insignificant variables no
Reviewed by LCM

Abstract

Increasing the share of battery electric vehicles (BEV) in the total car fleet is regarded as a promising way to reduce local car emissions. Based on online surveys in Denmark and Sweden, this study compares BEV users' (n = 673) and conventional vehicle (CV) users' (n = 1794) socio-demographic profiles, attitudinal profiles, and mobility patterns. In line with previous research, BEV users are typically male, highly educated, have high incomes, and often more than one car in their household. Additionally, BEV users perceive less functional barriers toward BEV use and have more positive attitudes and norms than CV users. The different profiles of these user groups suggest a separate analysis of potential factors of BEV adoption in both groups. In regression analyses, CV and BEV users' intention to use/purchase a BEV is modeled based on factors of the Theory of Planned Behavior extended by personal norm, perceived mobility necessities, and BEV experience. For CV users, symbolic attitudes related to BEVs are the most important factor of intention, while perceived functional barriers in terms of driving range are most relevant for BEV users' intention. How BEV users cope with trips of longer distance seems of particular relevance. In multiple car households, we found the percentage of actual BEV usage related to the type of other cars in the household, perceived functional barriers of BEVs as well as (successful) behavioral adaption to longer trips by BEVs. Based on the results, we discuss ways to increase BEV adoption for current users and non-users. © 2018, © 2018 Taylor & Francis Group, LLC.

Factors

Variable Pattern loading
It is fun to drive an electric car (Mode-liking) 0.744
The fast acceleration of an electric car is an exciting experience (Mode-liking) 0.833
I'm fascinated by the technology of electric cars (Lifestyle) 0.647
Variable Pattern loading
I (would) feel embarrassed when driving an electric car (Social norms) -0.631
I (would) feel proud of having an electric car (Social norms) 0.656
Driving an electric car expresses (my) environmental awareness (Environmentalism) 0.785
Driving an electric car expresses (my) openness for new technologies (Lifestyle) 0.707
Variable Pattern loading
The organization of my everyday life requires a high level of mobility (Lifestyle) 0.902
I have to be mobile all the time to meet my obligations (Lifestyle) 0.894
The possibility to change my plans spontaneously is very important to me (Convenience) 0.75
Variable Pattern loading
The need for charging makes electric cars very unpractical for use in everyday life (Convenience) 0.775
Ensuring that an electric car is always charged makes it inconvenient to use (Res preference/perception) 0.787
Using an electric car requires a careful planning of activities (Convenience) 0.782
When driving an electric car, I'm always (would always be) worried about running out of charge (Convenience) 0.767
Using an electric car for longer distances is difficult due to a lack of charging stations along the motorway (Convenience) 0.745
Variable Pattern loading
If I buy a car, I feel morally obliged to choose a car that minimizes carbon emissions and air pollution (Environmentalism) 0.871
I feel obliged to take environmental consequences of vehicle use into account when choosing a car (Environmentalism) 0.856
Variable Pattern loading
People who are important to me are considering to buy an electric car (Social norms) 0.832
People who are important to me own an electric car (Social norms) 0.82
People who are important to me think my next car should be an electric car (Social norms) 0.78
People who are important to me think that electric cars should play an important role in our transport system (Social norms) 0.715

Models

Dependent variable Intention to buy/use a BEV
Model type Linear regression
Sample size 1794.0
R2 0.558
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence nan
Variable Coefficient p-value
Perceived functional barriers -0.236 0
Attitude: symbolic 0.31 0
Attitude: affective 0.24 0
Subjective norm 0.183 0
Personal norm 0.113 0
Busy lifestyle -0.017 0.423
Satisfaction with price/public incentives 0.065 0.007
Satisfaction with maintenance costs 0.033 0.209
Satisfaction with environmental performance 0.011 0.642
Dependent variable Intention to buy/use a BEV
Model type Linear regression
Sample size 1794.0
R2 0.582
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence nan
Variable Coefficient p-value
Perceived functional barriers -0.219 0
Attitude: symbolic 0.316 0
Attitude: affective 0.196 0
Subjective norm 0.18 0
Personal norm 0.122 0
Busy lifestyle -0.039 0.084
Satisfaction with price/public incentives 0.075 0.002
Satisfaction with maintenance costs 0.024 0.369
Satisfaction with environmental performance 0.018 0.469
Age 0.138 0.346
Age2 -0.208 0.156
Gender -0.09 0
Income 0.001 0.964
University education 0.046 0.039
Self-employed 0.02 0.338
Total number of household members -0.019 0.496
Number of children under 10 years in HH -0.02 0.456
Country: Sweden (reference: Denmark) 0.086 0
Number of cars in household 0.012 0.599
Access to a private parking place 0.05 0.026
Ever travelled in BEV? 0.033 0.167
Ever recharged a battery electric car? -0.001 0.966
Dependent variable Intention to buy/use a BEV
Model type Linear regression
Sample size 673.0
R2 0.406
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence nan
Variable Coefficient p-value
Perceived functional barriers -0.341 0
Attitude: symbolic 0.213 0
Attitude: affective 0.224 0
Subjective norm 0.091 0.006
Personal norm 0.041 0.263
Busy lifestyle -0.059 0.061
Satisfaction with price/public incentives 0.033 0.281
Satisfaction with maintenance costs -0.003 0.928
Satisfaction with environmental performance 0.08 0.025
Dependent variable Intention to buy/use a BEV
Model type Linear regression
Sample size 673.0
R2 0.442
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero nan
Log-likelihood at constants nan
Log-likelihood at convergence nan
Variable Coefficient p-value
Perceived functional barriers -0.326 0
Attitude: symbolic 0.181 0
Attitude: affective 0.222 0
Subjective norm 0.084 0.014
Personal norm 0.041 0.274
Busy lifestyle -0.044 0.191
Satisfaction with price/public incentives 0.009 0.782
Satisfaction with maintenance costs 0.012 0.721
Satisfaction with environmental performance 0.073 0.05
Age 0.229 0.343
Age2 -0.245 0.306
Gender 0.057 0.079
Income -0.036 0.327
University education -0.045 0.177
Self-employed 0.035 0.288
Total number of household members -0.085 0.055
Number of children under 10 years in HH 0.047 0.272
Country: Sweden (reference: Denmark) 0.084 0.03
Number of cars in household -0.014 0.744
Gasoline/diesel car -0.047 0.276
BEV is a Tesla 0.038 0.252
Access to a private parking place -0.043 0.201
Change: Plan longer trips more carefully 0.072 0.04
Change: I do not travel long distances by car anymore -0.071 0.05
Change: I use other modes of transport more often 0.035 0.315
Change: I use other modes of transport less often -0.036 0.284

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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