Assessment of Athens's metro passenger behaviour via a multiranked probit model

Summary. We deal with real data from a stated preference experiment which was designed to explain and predict passengers’ behaviour towards three main means of transportation in the city of Athens. The resulting model formulations give rise to the so‐called multiranked probit model which emerges from a series of ranking responses in a set of hypothetical scenarios, i.e. we enhance the multinomial probit model with the embodiment of a utility threshold parameter which deals realistically with ranking responses, intransitivity of indifference between alternatives or ties. Moreover, we ensure identifiable parameters for the covariance matrix of the underlying utility vectors, we include a hierarchical step that models the unit‐specific utility thresholds as exchangeably distributed and, finally, we permit the use of heavy‐tailed distributions for the stochastic error term. Our proposed methodology is Bayesian and the implementation tool adopted is Markov chain Monte Carlo sampling. The posterior output consists of practical information such as travel characteristics (e.g. walking times and waiting times), expressed either in drachmas per hour or in minutes of in‐vehicle time, and 95% credible intervals of the probability of choosing a particular mode of transportation. These are key factors in determining whether a policy has positive or negative net benefits.