Exploring the Influence of Attitudes to Walking and Cycling on Commute Mode Choice Using a Hybrid Choice Model
Ding, Chen, Duan, Lu, Cui, 2017, in Journal of Advanced Transportation
doi:10.1155/2017/8749040
| Location |
Zhenjiang City, China |
| Population |
General |
| Sample size |
1110 |
| Factor analysis type |
confirmatory factor analysis, nan rotation |
| Stepwise regression |
no |
| Removal of insignificant variables |
no |
| Reviewed by |
LCM |
Abstract
Transport-related problems, such as automobile dependence, traffic congestion, and greenhouse emissions, lead to a great burden on the environment. In developing countries like China, in order to improve the air quality, promoting sustainable travel modes to reduce the automobile usage is gradually recognized as an emerging national concern. Though there are many studies related to the physically active modes (e.g., walking and cycling), the research on the influence of attitudes to active modes on travel behavior is limited, especially in China. To fill up this gap, this paper focuses on examining the impact of attitudes to walking and cycling on commute mode choice. Using the survey data collected in China cities, an integrated discrete choice model and the structural equation model are proposed. By applying the hybrid choice model, not only the role of the latent attitude played in travel mode choice, but also the indirect effects of social factors on travel mode choice are obtained. The comparison indicates that the hybrid choice model outperforms the traditional model. This study is expected to provide a better understanding for urban planners on the influential factors of green travel modes. © 2017 Chuan Ding et al.
Factors
Models
| Dependent variable |
Active commute mode |
| Model type |
Discrete choice |
| Sample size |
1110.0 |
| R2 |
nan |
| Adjusted R2 |
|
|
Pseudo R2
(nan)
|
nan |
| AIC |
8600.808 |
| BIC |
8670.571 |
| Log-likelihood at zero |
nan |
| Log-likelihood at constants |
nan |
| Log-likelihood at convergence |
nan |
| Variable |
Coefficient |
p-value |
| Constant |
0.547
|
0.0 |
| Household children |
-0.058
|
0.05 |
| Bicycle ownership |
0.243
|
0.0 |
| Car ownership |
-0.046
|
0.142 |
| Bus card |
-0.042
|
0.149 |
| Drivers' license |
-0.064
|
0.036 |
| Gender |
0.016
|
0.567 |
| Age 1 (below 35) |
0.115
|
0.001 |
| Age 3 (over 55) |
0.059
|
0.037 |
| Education 1 (low - junior school) |
0.005
|
0.105 |
| Education 3 (high - bachelor, master, or Ph.D.) |
0.089
|
0.006 |
| Government |
-0.054
|
0.049 |
| Income 1 (less than 2000 Y) |
0.171
|
0.0 |
| Income 3 (more than 8000 Y) |
-0.011
|
0.693 |
| Dependent variable |
Active commute mode |
| Model type |
Hybrid choice |
| Sample size |
1110.0 |
| R2 |
nan |
| Adjusted R2 |
|
|
Pseudo R2
(nan)
|
nan |
| AIC |
8267.361 |
| BIC |
8311.986 |
| Log-likelihood at zero |
nan |
| Log-likelihood at constants |
nan |
| Log-likelihood at convergence |
nan |
| Variable |
Coefficient |
p-value |
| Constant |
0.547
|
0.0 |
| Household children |
-0.058
|
0.049 |
| Bicycle ownership |
0.245
|
0.0 |
| Car ownership |
-0.045
|
0.153 |
| Bus card |
-0.043
|
0.138 |
| Drivers' license |
-0.066
|
0.032 |
| Gender |
0.013
|
0.625 |
| Age 1 (below 35) |
0.113
|
0.001 |
| Age 3 (over 55) |
0.059
|
0.04 |
| Education 1 (low - junior school) |
0.053
|
0.087 |
| Education 3 (high - bachelor, master, or Ph.D.) |
0.087
|
0.007 |
| Government |
-0.056
|
0.042 |
| Income 1 (less than 2000 Y) |
0.165
|
0.0 |
| Income 3 (more than 8000 Y) |
-0.013
|
0.651 |
| Attitude towards nonmotorized travel |
0.056
|
0.095 |