Hybrid Choice Models: Progress and Challenges

Moshe Ben-Akiva; Daniel Mcfadden; Kenneth Train; Joan Walker; Chandra Bhat; Michel Bierlaire; Denis Bolduc; Axel Boersch-Supan; David Brownstone; David S. Bunch; Andrew Daly; Andre De Palma; Dinesh Gopinath; Anders Karlstrom; Marcela A. Munizaga

doi:10.1023/A:1020254301302

Hybrid Choice Models: Progress and Challenges

Moshe Ben-Akiva, Daniel Mcfadden, Kenneth Train, Joan Walker, Chandra Bhat, Michel Bierlaire, Denis Bolduc, Axel Boersch-Supan, David Brownstone, David S. Bunch, Andrew Daly, Andre De Palma, Dinesh Gopinath, Anders Karlstrom, Marcela A. Munizaga

Research output: Contribution to journal › Article › peer-review

536 Scopus citations

Abstract

We discuss the development of predictive choice models that go beyond the random utility model in its narrowest formulation. Such approaches incorporate several elements of cognitive process that have been identified as important to the choice process, including strong dependence on history and context, perception formation, and latent constraints. A flexible and practical hybrid choice model is presented that integrates many types of discrete choice modeling methods, draws on different types of data, and allows for flexible disturbances and explicit modeling of latent psychological explanatory variables, heterogeneity, and latent segmentation. Both progress and challenges related to the development of the hybrid choice model are presented.

Original language	English
Pages (from-to)	163-175
Number of pages	13
Journal	Marketing Letters
Volume	13
Issue number	3
DOIs	https://doi.org/10.1023/A:1020254301302
State	Published - 2002
Externally published	Yes

Keywords

Choice modeling
Estimation
Latent variables
Logit kernel
Mixed logit
Simulation

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abstract = "We discuss the development of predictive choice models that go beyond the random utility model in its narrowest formulation. Such approaches incorporate several elements of cognitive process that have been identified as important to the choice process, including strong dependence on history and context, perception formation, and latent constraints. A flexible and practical hybrid choice model is presented that integrates many types of discrete choice modeling methods, draws on different types of data, and allows for flexible disturbances and explicit modeling of latent psychological explanatory variables, heterogeneity, and latent segmentation. Both progress and challenges related to the development of the hybrid choice model are presented.",

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T2 - Progress and Challenges

AU - Ben-Akiva, Moshe

AU - Mcfadden, Daniel

AU - Train, Kenneth

AU - Walker, Joan

AU - Bhat, Chandra

AU - Bierlaire, Michel

AU - Bolduc, Denis

AU - Boersch-Supan, Axel

AU - Brownstone, David

AU - Bunch, David S.

AU - Daly, Andrew

AU - De Palma, Andre

AU - Gopinath, Dinesh

AU - Karlstrom, Anders

AU - Munizaga, Marcela A.

PY - 2002

Y1 - 2002

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AB - We discuss the development of predictive choice models that go beyond the random utility model in its narrowest formulation. Such approaches incorporate several elements of cognitive process that have been identified as important to the choice process, including strong dependence on history and context, perception formation, and latent constraints. A flexible and practical hybrid choice model is presented that integrates many types of discrete choice modeling methods, draws on different types of data, and allows for flexible disturbances and explicit modeling of latent psychological explanatory variables, heterogeneity, and latent segmentation. Both progress and challenges related to the development of the hybrid choice model are presented.

KW - Choice modeling

KW - Estimation

KW - Latent variables

KW - Logit kernel

KW - Mixed logit

KW - Simulation

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VL - 13

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EP - 175

JO - Marketing Letters

JF - Marketing Letters

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Hybrid Choice Models: Progress and Challenges

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Keywords

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