Factors affecting electric vehicle sharing program participants' attitudes about car ownership and program participation
Kim, Ko, Park, 2015, in Transportation Research Part D: Transport and Environment
doi:10.1016/j.trd.2015.02.009
Location |
Seoul |
Population |
General |
Sample size |
533 |
Factor analysis type |
exploratory factor analysis, varimax rotation |
Stepwise regression |
yes |
Removal of insignificant variables |
yes |
Reviewed by |
LCM |
Abstract
There are growing concerns on traffic congestion, climate change and parking problems in major cities. Faced with these concerns, policy makers have sought sustainable transportation options including electric vehicle sharing programs (EVSPs). The city of Seoul with 10 million people also has recently launched an EVSP to provide citizens with an alternative travel mode. This study attempts to explore factors affecting the EVSP participants' attitudes about car ownership and program participation. To do this, a web-based survey was conducted for the participants of the Seoul EVSP, asking their satisfaction levels for the components of the EVSP. Then, using 533 responses of 1772 EVSP members (a response rate of 30%), ordered probit models were developed for three types of attitudes: (1) willingness to dispose of a car, (2) willingness to purchase an EV and (3) willingness to continue participating in the EVSP. The estimated models suggested that participants' social and economic perspectives were the most important factors affecting the participants' attitudes. In addition, the attitudes varied depending on personal characteristics such as gender, age and income. Although this study was conducted in the early stage of an EVSP, its results are expected to provide insights into a better EVSP design. © 2015 Elsevier Ltd.
Factors
Models
Dependent variable |
Will dispose of a current vehicle |
Model type |
ordered probit |
Sample size |
533.0 |
R2 |
nan |
Adjusted R2 |
|
Pseudo R2
(nan)
|
nan |
AIC |
nan |
BIC |
nan |
Log-likelihood at zero |
nan |
Log-likelihood at constants |
-727.57 |
Log-likelihood at convergence |
-699.94 |
Variable |
Coefficient |
p-value |
Booking, fee, and payment |
0.087
|
<0.1 |
Social and economic perspective |
0.162
|
<0.01 |
Age |
0.19
|
<0.01 |
Income |
-0.068
|
<0.05 |
Car owner |
-0.285
|
<0.01 |
Single |
0.266
|
<0.05 |
Non-office job |
0.368
|
<0.05 |
Threshold T1 |
-0.651
|
nan |
Threshold T2 |
0.466
|
nan |
Threshold T3 |
1.565
|
nan |
Threshold T4 |
2.112
|
nan |
Dependent variable |
Will purchase an EV |
Model type |
ordered probit |
Sample size |
533.0 |
R2 |
nan |
Adjusted R2 |
|
Pseudo R2
(nan)
|
nan |
AIC |
nan |
BIC |
nan |
Log-likelihood at zero |
nan |
Log-likelihood at constants |
-766.4 |
Log-likelihood at convergence |
-744.72 |
Variable |
Coefficient |
p-value |
Shared EVs |
0.126
|
<0.01 |
Renting, charging, and driving |
0.156
|
<0.01 |
Social and economic perspective |
0.187
|
<0.01 |
Age |
0.132
|
<0.05 |
Income |
-0.068
|
<0.05 |
Car owner |
0.223
|
<0.05 |
Threshold T1 |
-1.184
|
nan |
Threshold T2 |
-0.228
|
nan |
Threshold T3 |
0.862
|
nan |
Threshold T4 |
1.73
|
nan |
Dependent variable |
Will continue participating in the EVSP |
Model type |
ordered probit |
Sample size |
533.0 |
R2 |
nan |
Adjusted R2 |
|
Pseudo R2
(nan)
|
nan |
AIC |
nan |
BIC |
nan |
Log-likelihood at zero |
nan |
Log-likelihood at constants |
-734.7 |
Log-likelihood at convergence |
-666.18 |
Variable |
Coefficient |
p-value |
Shared EVs |
0.138
|
<0.01 |
Booking, fee, and payment |
0.268
|
<0.01 |
Renting, charging, and driving |
0.226
|
<0.01 |
Social and economic perspective |
0.298
|
<0.01 |
Female |
0.294
|
<0.05 |
Age |
0.187
|
<0.05 |
Income |
-0.056
|
<0.05 |
Single |
0.209
|
<0.1 |
Non-office job |
0.38
|
<0.05 |
University student |
0.355
|
<0.05 |
Leisure |
0.332
|
<0.01 |
Personal usage |
0.302
|
<0.05 |
Threshold T1 |
-1.763
|
nan |
Threshold T2 |
-0.755
|
nan |
Threshold T3 |
0.457
|
nan |
Threshold T4 |
1.569
|
nan |