Developing econometric models to forecast the demand for a shared-ride taxi : an application to an organization-based context -

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. Providing an efficient shared-ride transport system requires judicious planning, especially that pertaining to the study of users’ travel demand and behavior. The purpose of this thesis is to evaluate the market demand potential of a Shared-Ride Taxi (SRT) service in an organization-based context. It presents a modeling framework that extends the transportation literature to include the estimation of both: discrete choice and count data models and using appropriate selection criteria, it concludes with the best fitting model, through which analysis is done. The modeling framework incorporates the level of service attributes of the Shared-Ride Taxi (e.g. fare, vehicle size, and internet availability), the socioeconomic characteristics of the users, as well as their attitudes towards ridesharing and technology. Following model estimation, one model (proving the best inference and fit) is applied to predict the SRT ridership (characterized by the percentage of students willing to use the SRT) and examine how the latter varies with variation in the values of the attributes of the new taxi service. The study involves extensive analysis of practical policy scenarios through which the impact of cost incentives (subsidies) and multiple Shared-Ride Taxi attributes on travelers’ behavior is examined. Using Stated Preference (SP) data, the evaluation sheds light on the case of the students at the American University of Beirut. Research results can be used as an initial step towards studying the market potential of a Shared-Ride Taxi in a university setting in Lebanon. Results reveal that 30percent to 50percent of the students