This paper presents, discusses and tests a generalized Random Regret Minimization (G-RRM) model. The G-RRM model is created by replacing a fixed constant in the attribute-specific regret functions of the RRM model, by a regret-weight variable. Depending on the value of the regret-weights, the...

This paper investigates the potential of association rules learning and random forests to analyse data from complex choice experiments, and to obtain relevant insights for choice modellers and practitioners. We apply these data-driven methods on data from a so-called Participatory Value...

During the past 40 years, mobility patterns have enduringly changed several times as a result of the occurrence of a number “substantial changes”. Examples of such substantial changes are the rapid emergence of affordable air travel, the oil crises, and profound ICT developments. To most...

This paper presents an overview of model properties and empirical evidence related to the recently introduced discrete choice paradigm of random regret minimization (RRM). The RRM approach to discrete choice modelling provides an alternative to the conventional, linear-additive random utility...

Accessibility is a concept central to integrated transport and land use planning. The goal of improving accessibility for all modes, for all people, has made its way into mainstream transport policy and planning in communities worldwide. This unique and fascinating book introduces new...

This paper presents, discusses and tests a generalized Random Regret Minimization (G-RRM) model. The G-RRM model is created by replacing a fixed constant in the attribute-specific regret functions of the RRM model, by a regret-weight variable. Depending on the value of the regret-weights, the...