Hybrid choice models: Progress and challenges

被引：502

作者：

Ben-Akiva, M

Mcfadden, D

Train, K

Walker, J

Bhat, C

Bierlaire, M

Bolduc, D

Boersch-Supan, A

Brownstone, D

Bunch, DS

Daly, A

De Palma, A

Gopinath, D

Karlstrom, A

Munizaga, MA

机构：

[1] MIT, Cambridge, MA 02139 USA

[2] Univ Calif Berkeley, Berkeley, CA 94720 USA

[3] Univ Texas, Austin, TX 78712 USA

[4] Ecole Polytech Fed Lausanne, Lausanne, Switzerland

[5] Univ Laval, Quebec City, PQ G1K 7P4, Canada

[6] Univ Mannheim, D-6800 Mannheim 1, Germany

[7] Univ Calif Irvine, Irvine, CA 92717 USA

[8] Univ Calif Davis, Davis, CA 95616 USA

[9] Univ Cergy Pontoise, Cergy Pontoise, France

[10] Mercer Management Consulting, New York, NY 10036 USA

[11] Royal Inst Technol, Stockholm, Sweden

[12] Univ Chile, Santiago, Chile

来源：

MARKETING LETTERS | 2002年 / 13卷 / 03期

关键词：

choice modeling; mixed logit; logit kernel; simulation; estimation; latent variables;

D O I：

10.1023/A:1020254301302

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

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.

引用

页码：163 / 175

页数：13

共 28 条

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