Accommodating exogenous variable and decision rule heterogeneity in discrete choice models: Application to bicyclist route choice.

ABSTRACT: The proposed research contributes to our understanding of incorporating heterogeneity in discrete choice models with respect to exogenous variables and decision rules. Specifically, the proposed latent segmentation based mixed models segment population to different classes with their own decision rules while also incorporating unobserved heterogeneity within the segment level models. In our analysis, we choose to consider both random utility and random regret theories. Further, instead of assuming the number of segments (as 2), we conduct an exhaustive exploration with multiple segments across the two decision rules. The model estimation is conducted using a stated preference data from 695 commuter cyclists compiled through a web-based survey. The probabilistic allocation of respondents to

SUBMITTER: Dey BK 

PROVIDER: S-EPMC6268012 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature