Context-driven regret-based model of travel behavior under uncertainty: a latent class approach

Understanding variability in observed travel behavior has been one of the major research topics in travel behavior analysis and travel demand modeling. Differences in outcomes of travel decisions can be attributed to observed and non-observed differences between travelers and different situations and contexts in which decisions are made. The majority of studies in transportation research have estimated the effects of observed socio-demographic profiles on choice probabilities under certainty. Unobserved heterogeneity in utility functions has been typically examined using mixed logit or latent class models. The focus of the current paper concerns the effect of context and personality traits on decision-making under uncertainty, a combination of factors that has received not much attention in transportation research to date. Using route choice in an activity context as an example, we estimate a latent class random regret-minimization model, which takes into account the travel time and therefore arrival time uncertainty that people face when making route choice decisions. In addition, it incorporates the effects of personality traits, socio-demographic profiles and contextual factors, which increase or decrease travelers' feelings of regret. The model is estimated based on a stated choice experiment, which was administered through a Web-based survey. Results suggest the existence of three latent classes underlying differences in regret-driven choice behavior.