Hybrid Choice Modeling of New Technologies for Car Choice in Canada. Transportation Research Record

In the last decade, a new trend in discrete choice modeling has emerged in which psychological factors are explicitly incorporated in order to enhance the behavioral representation of the choice process. In this context, Hybrid Models expand on standard choice models by including attitudes and perceptions as latent variables. The complete model is composed of a group of structural equations describing the latent variables in terms of observable exogenous variables, and a group of measurement relationships linking latent variables to certain observable indicators. Although the estimation of Hybrid Models requires the evaluation of complex multi-dimensional integrals, simulated maximum likelihood is implemented in order to solve the integrated multi-equation model. In this paper we study empirically the application of Hybrid Choice Modeling to data from a survey conducted by the EMRG (Simon Fraser University, 2002-2003) of virtual personal vehicle choices made by Canadian consumers when faced with technological innovations. The survey also includes a complete list of indicators, allowing us to apply a Hybrid Choice Model formulation. We conclude that Hybrid Choice is genuinely capable of adapting to practical situations by including latent variables among the set of explanatory variables. Incorporating perceptions and attitudes in this way leads to more realistic models and gives a better description of the profile of consumers and their adoption of new private transportation technologies.