Abstract Ridesplitting, despite having been around for years, accounts for a low proportion of overall transportation modes. With the development of technology, app-based ridesplitting is witnessing new opportunities but its usage rate still remains poor. Intuitively, travelers’ aversion to the unreliable travel time inherent of ridesplitting may stop them from choosing it. Many studies have explored the role of risk aversion, but fewer focus on ambiguity aversion. In this study, we aim to understand travelers’ preferences for information ambiguity in shaping their choice behavior of using app-based ridesplitting. Therefore, we built up choice models of this thought to describe travelers’ behaviors in ridesplitting. Based on the models, a two-stage framework was established including field data research and experimental research testing the existence of ambiguity aversion. In the first stage, a data set containing detailed information on nearly 2.2 million trips in Chengdu, China was utilized. By the maximum likelihood method, the fitting level of unreliability model is better and the coefficient of ambiguity attitude shows the existence of ambiguity aversion. In the second stage, a stated choice experiment was designed with a variety of choice tasks to reproduce real-life scenarios. Significantly fewer ridesplitting cases happen in the ambiguous information treatment than in the certain information treatment, but risky information does not reduce the number of choosing ridesplitting significantly. The results undergo cross-validation with field research data to ensure their reliability. This study leverages travelers’ aversion to ambiguity to explain their reluctance towards ridesplitting. The findings have strong implications for relevant service platforms to prompt more travelers towards participating in ridesplitting, for example enhancing the provision of travel information to address the concerns of potential users.
Highlights We proved that travelers exhibit an aversion to ambiguous information in the usage of ridesplitting. A two-stage study was conducted: field data research, and experimental research. We measured travelers’ attitude towards ambiguity and risk using Maximum Likelihood Estimation (MLE).
A barrier to the promotion of app-based ridesplitting: Travelers’ ambiguity aversion in mode choice
2024-01-07
Article (Journal)
Electronic Resource
English
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