Modeling the demand for a shared-ride taxi service: An application to an organization-based context: Fid-Bau Portal

Modeling the demand for a shared-ride taxi service: An application to an organization-based context

Al-Ayyash, Zahwa / Abou-Zeid, Maya / Kaysi, Isam

Abstract Traffic congestion has become a worldwide concern. One way to address this problem is to enhance the performance of the transport system by means of sound public transportation that is capable of appropriately addressing the demand of travelers, especially in highly urbanized areas of the world. The implementation of shared-ride transportation has been a viable transportation solution in many areas. The purpose of this study is to evaluate the market demand potential of a Shared-Ride Taxi (SRT) service in an organization-based context. It presents an integrated choice and latent variable modeling framework for modeling the number of times per week a Shared-Ride Taxi would be used if it were implemented at an organization. The study involves extensive analysis of practical policy scenarios through which the impact of cost incentives (subsidies) and multiple SRT attributes on travelers’ behavior is examined. Using stated preference data, the model is applied to a case study of the students at the American University of Beirut in Lebanon. Research results are expected to provide an initial evaluation of the market potential for a Shared-Ride Taxi in a university setting in Lebanon. Results reveal that 30–50% of the students are willing to utilize the Shared-Ride Taxi service under practical scenarios and that subsidies are likely to play a key role in increasing the SRT ridership.

Highlights • A modeling framework is proposed to predict the demand for a Shared-Ride Taxi. • An Integrated Choice and Latent Variable model was used to model the taxi ridership. • The framework was applied to the students of American University of Beirut. • Subjective factors such as attitudes towards ridesharing impact ridership. • Results also showed that subsidies are likely to play a key role in increasing ridership.