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- W636542496 abstract "Traditional discrete choice models consider only objective attributes from the alternatives as explanatory variables. Modeling the choice of transport mode is a central element in travel demand estimation. Traditional modeling has used mainly objective modal attributes, such as travel times and cost, as explanatory variables. Nevertheless, it is well known that attitudes and perceptions may also influence users’ behavior. The use of hybrid discrete choice models constitutes a good alternative to incorporate the effect of these subjective factors, as they allow the inclusion of both tangible alternative attributes and latent variables associated with attitudes and perceptions. Data available to us, in a panel context, included users’ perception about some aspects of their available transport modes and allowed us to generate indicators of these perceptions. With this data we estimated hybrid discrete choice models in a panel context. This paper analyses the results of applying hybrid discrete choice models to a real urban study case, with several alternatives, and also an approach to forecast using these models. The authors results clearly show that hybrid models are superior to traditional models hat ignore the effect of subjective attitudes and perceptions." @default.
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- W636542496 date "2009-01-01" @default.
- W636542496 modified "2023-09-27" @default.
- W636542496 title "Modelling and Forecasting with Latent Variables in Discrete Choice Panel Models" @default.
- W636542496 hasPublicationYear "2009" @default.
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