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.
