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Inclusion of latent variables in Mixed Logit models: Modelling and forecasting
AbstractTravel demand models typically use mainly objective modal attributes as explanatory variables. Nevertheless, it has been well known for many years that attitudes and perceptions also influence users’ behaviour. The use of hybrid discrete choice models constitutes a good alternative to incorporate the effect of subjective factors. We estimated hybrid models in a short-survey panel context for data among many alternatives. The paper analyses the results of applying these models to a real urban case study, and also proposes an approach to forecasting using these models. Our results show that hybrid models are clearly superior to even highly flexible traditional models that ignore the effect of subjective attitudes and perceptions.
Inclusion of latent variables in Mixed Logit models: Modelling and forecasting
AbstractTravel demand models typically use mainly objective modal attributes as explanatory variables. Nevertheless, it has been well known for many years that attitudes and perceptions also influence users’ behaviour. The use of hybrid discrete choice models constitutes a good alternative to incorporate the effect of subjective factors. We estimated hybrid models in a short-survey panel context for data among many alternatives. The paper analyses the results of applying these models to a real urban case study, and also proposes an approach to forecasting using these models. Our results show that hybrid models are clearly superior to even highly flexible traditional models that ignore the effect of subjective attitudes and perceptions.
Inclusion of latent variables in Mixed Logit models: Modelling and forecasting
Yáñez, M.F. (author) / Raveau, S. (author) / Ortúzar, J. de D. (author)
Transportation Research Part A: Policy and Practice ; 44 ; 744-753
2010-07-24
10 pages
Article (Journal)
Electronic Resource
English
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