Electric vehicle development in Beijing: An analysis of consumer purchase intention

Huang, Xiangqian; Ge, Jianping, 2019, in Journal of Cleaner Production

doi:10.1016/j.jclepro.2019.01.231
Location Beijing, China
Population Other (specify)
Sample size 502
Factor analysis type confirmatory factor analysis, none rotation
Stepwise regression no
Removal of insignificant variables no
Reviewed by LCM

Abstract

To reduce energy consumption and environmental pollution, the Chinese government is vigorously promoting the adoption of electric vehicles (EVs). As one of the first demonstration and promotion cities for EVs in China, Beijing has played an important leading role in the promotion of EVs. Based on the theory of planned behavior (TPB), this study introduced consumer cognitive status, product perception, and incentive policy measures (non-monetary incentive policy measures and monetary incentive policy measures) to build a purchase intention influence mechanism model for EVs. A questionnaire survey was conducted from March to April of 2018 among potential consumers in Beijing. A total of 502 valid survey responses were obtained, and a structural equation model (SEM) was used for an empirical analysis of the factors influencing EV purchasing intention. The results show that attitude, perceived behavior control, cognitive status, product perception and monetary incentive policy measures have significant positive effects on consumers’ intentions to purchase EVs in Beijing. However, subjective norms and non-monetary incentive policy measures have no significant impact on purchasing intention. In addition, the analysis results of the multi-group SEM show that there are significant differences in demographic variables (gender, age, education level, income, and ownership of cars) in the path of consumer purchase intention. Implications for policy makers and scope for further research are discussed. © 2019 Elsevier Ltd

Factors

Variable Pattern loading
I think it is very necessary to use electric vehicles (Other) 0.777
I think buying an electric vehicle is a good choice (Other) 0.87
I support the country in introducing more policies to encourage individuals to purchase electric vehicles (Transport policy) 0.662
Variable Pattern loading
I have a certain understanding of the brand and product attributes of electric vehicles (Other) 0.912
I have a certain understanding of the relevant preferential policies for electric vehicles (Other) 0.792
Variable Pattern loading
Purchase subsidy (Price) 0.752
Increase EV purchase loan amounts (Price) 0.672
Tax exemption policy (Price) 0.855
Preferential insurance policy (Price) 0.887
Parking fee reduction (Price) 0.757
Congestion fee reduction (if congestion charge is imposed) (Price) 0.739
Variable Pattern loading
Separate allocations of EV license plates (Transport policy) 0.694
Abolishment of restriction on traffic of EV (Transport policy) 0.833
Variable Pattern loading
I can largely decide whether or not to buy an electric vehicle at home (Other) 0.708
I will have the ability to buy an electric vehicle in the future (Other) 0.763
I am confident that if I want to, I will definitely be able to choose an electric vehicle for my next purchase (Other) 0.719
Variable Pattern loading
Charging infrastructure (Convenience) 0.772
After-sales service (Convenience) 0.693
Safety and protection (Safety) 0.798
Cruising range (Convenience) 0.868
Charging time (Convenience) 0.842
Battery life (Convenience) 0.853
Variable Pattern loading
I look forward to more brands and models of electric vehicles to be introduced to the market (Other) 0.762
I will buy an electric vehicle in the future (Other) 0.823
If the electric vehicle is good, I would recommend friends around me to buy (Social norms) 0.848
Variable Pattern loading
If people around me use electric vehicles, this will prompt me to buy (Social norms) 0.75
People who have an influence on me (such as family and friends) think that I should buy an electric vehicle (Social norms) 0.838
News media propaganda will prompt me to buy an electric vehicle (Other) 0.805

Models

Source variable Target variable Effect p-value Effect type
Attitude Purchase intention 0.306 0 direct_effect
Subject norm Purchase intention -0.026 0.666 direct_effect
Perceived behavioral control Purchase intention 0.292 0 direct_effect
Cognitive status Purchase intention 0.08 0.04 direct_effect
Product attributes Purchase intention 0.26 0 direct_effect
Non-monetary incentives policy Purchase intention -0.008 0.892 direct_effect
Monetary incentives policy Purchase intention 0.228 0 direct_effect
Source variable Target variable Effect p-value Effect type
Attitude Purchase intention 0.341 <0.001 direct_effect
Subject norm Purchase intention -0.003 nan direct_effect
Perceived behavioral control Purchase intention 0.21 <0.05 direct_effect
Cognitive status Purchase intention 0.142 <0.01 direct_effect
Product attributes Purchase intention 0.269 <0.001 direct_effect
Non-monetary incentives policy Purchase intention -0.017 nan direct_effect
Monetary incentives policy Purchase intention 0.212 <0.01 direct_effect
Source variable Target variable Effect p-value Effect type
Attitude Purchase intention 0.298 <0.05 direct_effect
Subject norm Purchase intention -0.001 nan direct_effect
Perceived behavioral control Purchase intention 0.444 <0.001 direct_effect
Cognitive status Purchase intention -0.1 nan direct_effect
Product attributes Purchase intention 0.256 <0.001 direct_effect
Non-monetary incentives policy Purchase intention -0.072 nan direct_effect
Monetary incentives policy Purchase intention 0.297 <0.01 direct_effect
Source variable Target variable Effect p-value Effect type
Attitude Purchase intention 0.324 <0.001 direct_effect
Subject norm Purchase intention -0.007 nan direct_effect
Perceived behavioral control Purchase intention 0.281 <0.001 direct_effect
Cognitive status Purchase intention -0.011 nan direct_effect
Product attributes Purchase intention 0.337 <0.001 direct_effect
Non-monetary incentives policy Purchase intention -0.028 nan direct_effect
Monetary incentives policy Purchase intention 0.225 <0.01 direct_effect
Source variable Target variable Effect p-value Effect type
Attitude Purchase intention 0.249 <0.05 direct_effect
Subject norm Purchase intention 0.017 nan direct_effect
Perceived behavioral control Purchase intention 0.3 <0.001 direct_effect
Cognitive status Purchase intention 0.183 <0.01 direct_effect
Product attributes Purchase intention 0.151 <0.05 direct_effect
Non-monetary incentives policy Purchase intention 0.111 nan direct_effect
Monetary incentives policy Purchase intention 0.165 nan direct_effect
Source variable Target variable Effect p-value Effect type
Attitude Purchase intention 0.165 nan direct_effect
Subject norm Purchase intention 0.095 nan direct_effect
Perceived behavioral control Purchase intention -0.038 nan direct_effect
Cognitive status Purchase intention 0.292 nan direct_effect
Product attributes Purchase intention 0.214 <0.05 direct_effect
Non-monetary incentives policy Purchase intention -0.153 nan direct_effect
Monetary incentives policy Purchase intention 0.632 <0.01 direct_effect
Source variable Target variable Effect p-value Effect type
Attitude Purchase intention 0.285 <0.001 direct_effect
Subject norm Purchase intention -0.015 nan direct_effect
Perceived behavioral control Purchase intention 0.315 <0.001 direct_effect
Cognitive status Purchase intention 0.046 nan direct_effect
Product attributes Purchase intention 0.292 <0.05 direct_effect
Non-monetary incentives policy Purchase intention 0.021 nan direct_effect
Monetary incentives policy Purchase intention 0.163 <0.01 direct_effect
Source variable Target variable Effect p-value Effect type
Attitude Purchase intention 0.849 <0.05 direct_effect
Subject norm Purchase intention -0.372 nan direct_effect
Perceived behavioral control Purchase intention 0.249 nan direct_effect
Cognitive status Purchase intention -0.078 nan direct_effect
Product attributes Purchase intention 0.181 nan direct_effect
Non-monetary incentives policy Purchase intention 0.157 nan direct_effect
Monetary incentives policy Purchase intention 0.151 nan direct_effect
Source variable Target variable Effect p-value Effect type
Attitude Purchase intention 0.245 <0.01 direct_effect
Subject norm Purchase intention -0.012 nan direct_effect
Perceived behavioral control Purchase intention 0.327 <0.001 direct_effect
Cognitive status Purchase intention 0.077 nan direct_effect
Product attributes Purchase intention 0.255 <0.001 direct_effect
Non-monetary incentives policy Purchase intention -0.029 nan direct_effect
Monetary incentives policy Purchase intention 0.228 <0.001 direct_effect
Source variable Target variable Effect p-value Effect type
Attitude Purchase intention 0.552 <0.001 direct_effect
Subject norm Purchase intention -0.175 nan direct_effect
Perceived behavioral control Purchase intention 0.235 <0.01 direct_effect
Cognitive status Purchase intention -0.013 nan direct_effect
Product attributes Purchase intention 0.352 <0.001 direct_effect
Non-monetary incentives policy Purchase intention -0.12 nan direct_effect
Monetary incentives policy Purchase intention 0.307 <0.001 direct_effect
Source variable Target variable Effect p-value Effect type
Attitude Purchase intention 0.174 nan direct_effect
Subject norm Purchase intention 0.002 <0.01 direct_effect
Perceived behavioral control Purchase intention 0.4 <0.001 direct_effect
Cognitive status Purchase intention 0.049 <0.05 direct_effect
Product attributes Purchase intention 0.183 nan direct_effect
Non-monetary incentives policy Purchase intention 0.096 nan direct_effect
Monetary incentives policy Purchase intention 0.211 nan 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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