Perception towards electric vehicles and the impact on consumers’ preference
Ghasri, Ardeshiri, Rashidi, 2019, in Transportation Research Part D: Transport and Environment
doi:10.1016/j.trd.2019.11.003
Location |
New South Wales, Australia |
Population |
General |
Sample size |
1076 |
Factor analysis type |
exploratory factor analysis, unknown rotation |
Stepwise regression |
no |
Removal of insignificant variables |
yes |
Reviewed by |
LCM |
Abstract
Relative advantage, or the degree to which a new technology is perceived to be better than an existing technology which is being replaced, has a significant impact on individuals’ decisions on when, how and to what extent to adopt. An integrated choice and latent variable model is used, in this paper, to explicitly measure the perceived advantages in electric vehicles over the conventional internal combustion engine vehicles. The analysed data is obtained from a stated preference survey including 1076 residents in New South Wales, Australia. According to the results, the latent component of the model disentangles the perceived advantages across three dimensions of vehicle design, impact on the environment, and safety. These latent variables are interacted with price, driving range and body type, respectively, to capture the impact of perception on preference. The developed model is then used to examine the effectiveness of different support schemes on Millennials (Gen Y), the generation before them (Gen X) and after them (Gen Z). The results show higher probability of adopting electric vehicles for Gen Y, compared to Gen X and Z. Gen Y is found to be the least sensitive cohort to purchase price, and Gen X to be the most sensitive cohort to this attribute. People are more sensitive to incentives for the initial price compared to ongoing incentives for operating costs. Also, offering financial incentives to consumers as a rebate on the purchase price is more effective than allocating the same incentive to manufacturers to reduce the purchase price. © 2019 Elsevier Ltd
Factors
Models
Dependent variable |
Car choice |
Model type |
HCM |
Sample size |
1076 |
R2 |
0.373 |
Adjusted R2 |
|
Pseudo R2
(nan)
|
nan |
AIC |
nan |
BIC |
nan |
Log-likelihood at zero |
-148548.006 |
Log-likelihood at constants |
nan |
Log-likelihood at convergence |
-118279.273 |
Design |
Variable |
Coefficient |
p-value |
Constant |
2.78
|
0.0 |
Age |
-33.33
|
0.011 |
Age squared |
-8.71
|
0.002 |
Age cubed |
12.2
|
0.0 |
Female |
0.086
|
0.0 |
TAFE certificate or equivalent |
-0.15
|
0.0 |
Undergradaute |
0.196
|
0.0 |
Postgraduate |
0.444
|
0.0 |
Other education level |
0.0
|
nan |
Full time |
0.362
|
0.0 |
Part time |
0.122
|
0.0 |
Retired or unemployed |
0.0
|
nan |
Couple with kids |
0.49
|
0.0 |
Couple without kids |
-0.042
|
0.165 |
Single parent |
0.053
|
0.227 |
Single parent |
-0.128
|
0.0 |
Other household structure |
0.0
|
nan |
No vehicle |
0.0
|
nan |
1 vehicle |
-0.093
|
0.038 |
2 vehicles |
-0.207
|
0.0 |
3+ vehicles |
-0.317
|
0.0 |
Income below $54K |
0.409
|
0.0 |
Income above $104K |
0.038
|
0.062 |
House |
-0.047
|
0.088 |
Apartment |
-0.206
|
0.0 |
Owner |
0.524
|
0.0 |
Owner with mortgage |
0.349
|
0.0 |
Renter |
0.379
|
0.0 |
Environment |
Variable |
Coefficient |
p-value |
Constant |
3.79
|
0.0 |
Age |
-9.36
|
0.0 |
Age squared |
13.6
|
0.009 |
Age cubed |
-5.61
|
0.114 |
Female |
0.266
|
0.0 |
TAFE certificate or equivalent |
0.174
|
0.003 |
Undergradaute |
0.266
|
0.0 |
Postgraduate |
0.355
|
0.0 |
Other education level |
0.0
|
nan |
Full time |
0.155
|
0.0 |
Part time |
-0.065
|
0.126 |
Retired or unemployed |
0.0
|
nan |
Couple with kids |
0.431
|
0.0 |
Couple without kids |
0.283
|
0.0 |
Single parent |
0.209
|
0.008 |
Single parent |
0.363
|
0.0 |
Other household structure |
0.0
|
nan |
No vehicle |
0.0
|
nan |
1 vehicle |
-0.343
|
0.0 |
2 vehicles |
-0.379
|
0.0 |
3+ vehicles |
-0.217
|
0.027 |
Income below $54K |
0.017
|
0.66 |
Income above $104K |
0.111
|
0.004 |
House |
-0.161
|
0.002 |
Apartment |
-0.179
|
0.001 |
Owner |
-0.581
|
0.0 |
Owner with mortgage |
-0.585
|
0.0 |
Renter |
-0.568
|
0.0 |
Safety |
Variable |
Coefficient |
p-value |
Constant |
2.14
|
0.0 |
Age |
2.58
|
0.272 |
Age squared |
-27.5
|
0.0 |
Age cubed |
27.4
|
0.0 |
Female |
0.347
|
0.0 |
TAFE certificate or equivalent |
-0.053
|
0.358 |
Undergradaute |
0.157
|
0.008 |
Postgraduate |
0.736
|
0.0 |
Other education level |
0.0
|
nan |
Full time |
0.368
|
0.0 |
Part time |
0.354
|
0.0 |
Retired or unemployed |
0.0
|
nan |
Couple with kids |
0.665
|
0.0 |
Couple without kids |
-0.041
|
0.466 |
Single parent |
0.449
|
0.0 |
Single parent |
-0.019
|
0.749 |
Other household structure |
0.0
|
nan |
No vehicle |
0.0
|
nan |
1 vehicle |
-0.635
|
0.0 |
2 vehicles |
-0.954
|
0.0 |
3+ vehicles |
-1.34
|
0.0 |
Income below $54K |
0.396
|
0.0 |
Income above $104K |
0.067
|
0.074 |
House |
0.123
|
0.014 |
Apartment |
-0.05
|
0.353 |
Owner |
0.436
|
0.0 |
Owner with mortgage |
0.269
|
0.014 |
Renter |
0.205
|
0.06 |
Variable |
Coefficient |
p-value |
Hatchback |
0.49
|
0.954 |
Small sedan |
0.4417
|
0.954 |
Small SUV |
0.499
|
0.955 |
Purchase price |
-7.98
|
0.777 |
Setup cost |
-0.038
|
0.984 |
Operating costs |
-0.46
|
0.961 |
Recharge time |
-0.477
|
0.942 |
Rebate on upfront cost |
0.183
|
0.963 |
Energy bill discount until 2025 |
0.309
|
0.953 |
Portion of EVs sold (market share) |
0.344
|
0.958 |
Design*Purchase price |
2.38
|
0.925 |
Environment*Range in a single recharge |
0.023
|
0.997 |
Safety*Large SUV |
0.139
|
0.98 |
Safety*Large sedan |
0.084
|
0.981 |