The Benefits of Accounting for Respondent Heterogeneity in Choice Modeling (1998)

This paper demonstrates why recognizing differences between segments or respondents results in more predictive and valid choice simulations than simple aggregate models. Latent Class and ICE solutions are shown to better handle the traditional "Red bus/Blue bus" problem, cross-elasticities and interaction effects than the equivalent main-effects model using aggregate logit. Though cross-effects and IIA violations can be modeled in the aggregate, it requires modeling expertise and software other than CBC. The author concludes that it is beneficial to start with underlying utilities that are less susceptible to the "Red bus/Blue bus" problem.

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