Sequential Logit Approach to Modeling the Customer-Search Decisions of Taxi Drivers

Abstract

This paper develops an enhanced sequential logit model to depict the customer-search behavior of vacant-taxi drivers. This model considers that vacant-taxi drivers can change the choices that they make on their way to a designated district. Global positioning system trip data from 460 urban taxis were extracted to calibrate the model and to verify the factors underlying the drivers’ search decisions. The findings reveal that the proposed sequential logit model is capable of predicting the search paths of vacant-taxi drivers. This model form is considered to be more informative for policy makers who aim to study search paths and the associated traffic congestion contributed by taxis in each district.