Taking account of the role of safety on vehicle choice using a new generation of discrete choice models

被引:34
|
作者
Daziano, Ricardo A. [1 ]
机构
[1] Cornell Univ, Sch Civil & Environm Engn, Ithaca, NY 14853 USA
关键词
Vehicle choice; Latent variables; Car safety; Hybrid discrete choice; DEMAND;
D O I
10.1016/j.ssci.2011.07.007
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In attitudinal studies safety often appears as an important attribute desired by consumers when buying a new car (Ben-Akiva and Lerman, 1985). However, economic models of vehicle choice usually neglect the role of safety. On the one hand, to capture the qualitative nature of safety and variables related to safety one should consider safety as an underlying construct in a context of latent variable models. The problem is that psychometric models that make use of latent variables do not necessarily provide a complete understanding of agent behavior and may lead to poor predictive power. On the other hand, discrete choice models - although a powerful tool to explain decision making based on utility maximization behavior - fail to include qualitative factors as explanatory variables of the decision process. In this paper, we explore how to model safety through a new generation of discrete choice models which simultaneously consider both a standard discrete choice model and latent causal variables. Using stated preference data concerning purchase intentions of low-emission vehicles in Canada, we test a hybrid choice model to explain consumers' preferences for safety. Based on the results as well as on the hybrid choice modeling approach, we outline a general framework for the correct modeling of the adoption of safer vehicles and appreciation of safety equipment. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:103 / 112
页数:10
相关论文
共 50 条
  • [31] MODELING THE CHOICE OF CHOICE SET IN DISCRETE-CHOICE RANDOM-UTILITY MODELS
    HOROWITZ, JL
    ENVIRONMENT AND PLANNING A, 1991, 23 (09) : 1237 - 1246
  • [32] An analysis of accelerated vehicle retirement programs using a discrete choice personal vehicle model
    California Energy Commission, MS-22, 1516 9th Street, Sacramento, CA 95814, United States
    Transp. Policy, 2 (95-107):
  • [33] Testing probabilistic models of choice using column generation
    Smeulders, Bart
    Davis-Stober, Clintin
    Regenwetter, Michel
    Spieksma, Frits C. R.
    COMPUTERS & OPERATIONS RESEARCH, 2018, 95 : 32 - 43
  • [34] On substitutability and complementarity in discrete choice models
    Feng, Guiyun
    Li, Xiaobo
    Wang, Zizhuo
    OPERATIONS RESEARCH LETTERS, 2018, 46 (01) : 141 - 146
  • [35] The performance of bootstrapping in discrete choice models
    Baser, O
    VALUE IN HEALTH, 2006, 9 (03) : A102 - A102
  • [36] Taste variation in discrete choice models
    Chesher, A
    Silva, JMCS
    REVIEW OF ECONOMIC STUDIES, 2002, 69 (01): : 147 - 168
  • [37] Weak identification in discrete choice models
    Frazier, David T.
    Renault, Eric
    Zhang, Lina
    Zhao, Xueyan
    JOURNAL OF ECONOMETRICS, 2025, 248
  • [38] Heterogeneity in dynamic discrete choice models
    Browning, Martin
    Carro, Jesus M.
    ECONOMETRICS JOURNAL, 2010, 13 (01): : 1 - 39
  • [39] Resampling estimation of discrete choice models
    Ortelli, Nicola
    de Lapparent, Matthieu
    Bierlaire, Michel
    JOURNAL OF CHOICE MODELLING, 2024, 50
  • [40] Identification of Dynamic Discrete Choice Models
    Abbring, Jaap H.
    ANNUAL REVIEW OF ECONOMICS, VOL 2, 2010, 2 : 367 - 394