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A Before-and-after Study of Short-trip Driver’s Behavior Change Reacting to the Distance-based Toll Scheme
Distance-based Toll Scheme
Short-trip Road User’s Choice Behavior
Disaggregate Choice Model
This study happened to be in the year of the distance-based toll scheme being implemented. This study applied the conception of before-and-after analysis to explore how the new toll scheme influences short-trip road users’ choice behavior. As to the research method, binary logit model combining with latent variables was utilized to analyze the effects of basic attributes (e.g., trip attribute, social-economic attribute, cognitive latent variables, travel time, travel cost) on short-trip road users’ choice behavior. At last, the model of revealed preference with no latent variable was employed to analyze the variations in probability, elasticity and economic welfare before and after the distance-based toll scheme being implemented. The effective sample size of this study is 200. Among it, commuters occupy the proportion of 59%, and on the other hand, business trip is in the majority of non-commute purposes. The result shows that after the distance-based toll scheme, there are 98.5% participants remaining using freeway and 97% of them remain the same routes as past. According to the SEM before-model, every hypothesis is supported. The supported hypotheses are as follows: (H1) road users’ cognitive effect and efficiency of the distance-based toll scheme positively and directly affects their policy acceptance; (H2) road users’ cognitive fairness of the distance-based toll scheme positively and directly affects their policy acceptance; (H3) road users’ cognitive transference obstacle positively and directly affects their intention to remain using freeway; (H4) road users’ policy acceptance towards the distance-based toll scheme positively and directly affects their intention to remain using freeway. However, according to the SEM after-model, only H1, H2, H3 are supported while H4 is not supported. All the variables are significant in both binary logit model with and without latent variables, and the signs of same variables are consistent in before-model and after-model. The variables which influence route choice include alternative specific constant, travel time, travel cost, transference obstacle, policy acceptance, commute purpose, income and gender. As for other applied analysis, the result shows that after the distance-based toll scheme was conducted, the entire road users’ probability of using freeway increases; the entire elasticity is about -0.0374; the entire road user’s utility increases.
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