Public Preferences Towards Car Sharing Service: The Case of Djibouti

Abstract

Transportation demand management is a successful complement to urban infrastructure. The emergence of shared mobility strategies such as car sharing offers sustainable mobility in urban areas. Car sharing has launched in different cities worldwide to mitigate severe transportation problems such as traffic congestion, air pollution, and traffic safety. Therefore, this study aims to investigate the intentions and preferences of travelers toward car sharing services in Djibouti, Africa. The data was collected through an online stated preference (SP) survey. The SP survey included the awareness of car sharing services, attributes related to transport modes, and demographic characteristics. A total of 600 respondents were received. In this study, we employed the multinomial logit (MNL) model to travel mode choice modeling and compared the results with the AdaBoost algorithm. The MNL model results showed that generic attributes such as travel time, travel cost, maintenance charges, and membership fees were found significant. In addition, several demographic characteristics like gender, education, and income were also found significant. The modeling and prediction performances of the MNL model and AdaBoost algorithm were compared using multi-class predictive errors. According to the goodness-of-fit results, the AdaBoost algorithm achieved overall higher prediction accuracy than the MNL model. This study could be helpful to transport planners and policymakers for the implementation of car-sharing services in urban areas.