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dc.contributor.authorYutaka, Motoaki
dc.contributor.authorRicardo, Daziano
dc.date.accessioned2015-03-18T16:21:18Z
dc.date.available2015-03-18T16:21:18Z
dc.date.issued2015
dc.identifier.urihttps://hdl.handle.net/1813/39212
dc.description.abstractIn this paper we analyze demand for cycling using a discrete choice model with latent variables and a discrete heterogeneity distribution for the taste parameters. More specifically, we use a hybrid choice model where latent variables not only enter into utility but also inform assignment to latent classes. Using a discrete choice experiment we analyze the effects of weather (temperature, rain, and snow), cycling time, slope, cycling facilities (bike lanes), and traffic on cycling decisions by members of Cornell University (in an area with cold and snowy winters and hilly topography). We show that cyclists can be separated into two segments based on a latent factor that summarizes cycling skills and experience. Specifically, cyclists with more skills and experience are less affected by adverse weather conditions. By deriving the median of the ratio of the marginal rate of substitution for the two classes, we show that rain deters cyclists with lower skills from bicycling 2.5 times more strongly than those with better cycling skills. The median effects also show that snow is almost 4 times more deterrent to the class of less experienced cyclists. We also model the effect of external restrictions (accidents, crime, mechanical problems) and physical condition as latent factors affecting cycling choices.en_US
dc.description.sponsorshipThis research is based upon work supported by the University Transportation Research Center Region II, Grant NYSDOT ID 49997-35-24.en_US
dc.language.isoen_USen_US
dc.subjectdiscrete choiceen_US
dc.subjectcycling demanden_US
dc.subjecthybrid choiceen_US
dc.subjectdiscrete choice experimenten_US
dc.subjectactive transportationen_US
dc.subjectutilitarian cyclingen_US
dc.titleA hybrid-choice latent-class model for the analysis of the effects of weather on cycling demanden_US


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