Modeling the propensity to join carsharing using hybrid choice models and mixed survey data

详细信息    查看全文

• 作者：Dimitrios Efthymiou ; ^{defthym@mail.ntua.gr" class="auth_mail" title="E-mail the corresponding author} ; Constantinos Antoniou ^{antoniou@central.ntua.gr" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Carsharing ; Discrete choice models ; Latent classes ; Mixed internet/paper data ; Athens
• 刊名：Transport Policy
• 出版年：2016
• 出版时间：October 2016
• 年：2016
• 卷：51
• 期：Complete
• 页码：143-149
• 全文大小：615 K

文摘

Carsharing combines the positive elements of both private and public transportation. This feature renders it attractive to a significant percentage of the population, especially younger people who do not own a car. To maximize the effectiveness of such systems, the characteristics of potential users have been investigated in this research.

The propensity of people to join a carsharing scheme is being modeled using mixed data collected from Internet and paper surveys. An ordered logit model is developed to model the willingness of young Greeks to join carsharing. Several types of explanatory variables are used, including demographic characteristics and travel attributes, but also the satisfaction of the commuters about their current travel patterns, which is included as latent attitude in the modeling framework. The combination of the two datasets aims to measure the difference of the variance of the error term, generated from the paper and Internet respondents; the latter are prone to be more positive in their responses, possibly in order to satisfy the interviewer. This is verified in the current research by the positive sign of the scale parameter applied at the utility function of the Internet-based data. The use of latent classes enhances the model estimation, by measuring the parameters that determine the respondents' unobserved, underlying behaviors.

The results demonstrate that people who use taxi for social activities, those with medium to low income, and the environmentally conscious, are more willing to join a hypothetical carsharing scheme. The results are compared with a 2013 study, in order to identify the advantages of using this advanced modeling framework.