A hybrid choice model with nonlinear utility functions and bounded distributions for latent variables: application to purchase intention decisions of electric cars

J. Kim, S. Rasouli, H.J.P. Timmermans

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

The hybrid choice model (HCM) provides a powerful framework to account for heterogeneity across decision-makers in terms of different underlying latent attitudes. Typically, effects of the latent attitudes have been represented assuming linear utility functions. In contributing to the further elaboration of HCMs, this study suggests an extended HCM framework allowing for nonlinear utility functions of choice alternatives including not only observed but also latent variables. Box–Cox transformations are used to represent the nonlinear utility function. Johnson’s SB distribution is suggested to represent the random term of the latent variables, satisfying the constraint of the Box–Cox transformation. An empirical study using stated choice data about the intention to purchase electric cars is conducted. The empirical results show that the proposed framework can capture nonlinear effects of underlying variables including latent attitudes, thereby enhancing the explanatory power of the choice model.
Original languageEnglish
Title of host publicationProceedings of the 19th International Conference of Hong Kong Society for Transportation Studies, Hong Kong.
Publication statusPublished - 2014
Event19th International Conference of Hong Kong Society for Transportation Studies (HKSTS 2014) - Hong Kong, China
Duration: 13 Dec 201415 Dec 2014

Conference

Conference19th International Conference of Hong Kong Society for Transportation Studies (HKSTS 2014)
Abbreviated titleHKSTS2014
CountryChina
CityHong Kong
Period13/12/1415/12/14
OtherTransportation and Infrastructure

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