01557885

Component

There is growing interest in decision rule heterogeneity across individual respondents but also across attributes. This paper brings these two issues together by putting forward a latent class approach which not only allows for different decision rules across classes, but also differences in the decision rules used across attributes within a given class. To deal with the issue of the large number of possible combinations this produces, the authors focus on the specific case of random utility maximisation (RUM) and random regret minimisation (RRM) and put forward the use of a generalised random regret minimisation (G-RRM) model within individual classes. This allows the optimal specification in terms of split between RUM and RRM within a given class to be revealed by the data during estimation, rather than needing to be imposed by the analyst. Initial findings on a standard stated choice dataset are promising and show how a rich pattern of taste heterogeneity and decision rule heterogeneity across respondents and attributes can be revealed.

This paper was sponsored by TRB committee ADB10 Traveler Behavior and Values.

01550057

15-4315

English

15p

2015

Transportation Research Board 94th Annual Meeting

Digital/other

Figures; References; Tables

Choice models; Data files; Decision making; Discrete systems; Stated preferences; Stochastic processes; Travel behavior; Utility theory

Planning and Forecasting; Transportation (General); I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2015 Paper #15-4315

TRIS, TRB, ATRI

Dec 30 2014 1:25PM