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- W3146040643 abstract "This paper investigates the benefits of incorporating heteroscedastic stochastic distributions in random utility maximization-based multiple discrete-continuous (MDC) choice models. To this end, first, a Multiple Discrete Continuous Heteroscedastic Extreme Value (MDCHEV) model is formulated and compared with its predecessor, the Multiple Discrete-Continuous Extreme Value (MDCEV) model. Next, an empirical analysis of individuals’ daily time use choices is carried out using data from the National Household Travel Survey (NHTS) for three geographical regions in Florida. The MDCHEV parameter estimates revealed the significant presence of heteroscedasticity in the random utility components of different activity type choice alternatives. On the other hand, the MDCEV model resulted in inferior model fit and systematic discrepancies between the observed and predicted distributions of time allocations, which can be traced to the thick right tail of the type-1 extreme value distribution. The MDCHEV model addressed these issues to a considerable extent by allowing tighter stochastic distributions for certain choice alternatives, thanks to its accommodation of heteroscedasticity among random utility components. Spatial transferability assessments using different transferability metrics also suggest that the MDCHEV model clearly outperformed the MDCEV model." @default.
- W3146040643 created "2021-04-13" @default.
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- W3146040643 date "2014-01-01" @default.
- W3146040643 modified "2023-09-28" @default.
- W3146040643 title "The Benefits of Allowing Heteroscedastic Stochastic Distributions in Multiple Discrete-Continuous Choice Models" @default.
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