Delft University of Technology
August 09, 2011, 11:00, Room GC B3 424 (click here for the map)
This talk presents an overview of recent progress related to the recently introduced discrete choice-paradigm of Random Regret Minimization (RRM). The RRM-approach to discrete choice-modeling provides an alternative to the conventional, Random Utility Maximization (RUM)-based approach which has dominated the field since its inception. In contrast with RUM-theory, RRM-theory postulates that when choosing, decision-makers are concerned with avoiding the situation where one or more non-chosen alternatives perform better than a chosen one in terms of one or more attributes. From this central behavioral premise, semi-compensatory decision-making and choice set-composition effects like the compromise effect emerge as RRM-model features. Being as parsimonious as RUM�s linear-additive multinomial logit model, RRM features logit-choice-probabilities and is easily estimable using conventional discrete choice-software packages. This paper ties together the main insights and results from a number of recent studies that have explored RRM�s model properties and empirically tested RRM-based models vis-�-vis competing model forms. As such, the talk provides an assessment of RRM�s potential and its limitations as a discrete choice model.
Caspar Chorus is associate professor at Delft University of Technology (Section of Transport and Logistics). In past years, he was visiting scientist at Cornell University, assistant professor at Eindhoven University of Technology, visiting doctoral student at MIT and doctoral student at Delft University of Technology. His research is concerned with increasing the behavioral realism of travel demand models. The Random Regret Minimization-approach he developed has been succesfully applied in various research groups around the world, and is being incorporated in the newest version of the NLOGIT-software package. His 2007 dissertation �Traveler response to information� has been awarded, among other prizes, IATBR�s Eric Pas Prize.