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• W1988622014 abstract "As tour-based methods for activity and travel participation patterns replace trip-based methods, time-of-day (TOD) choice modeling remains problematic. In practice, most travel demand model systems handle tour scheduling via joint-choice multinomial logit (MNL) models, which suffer from the well-known independence of irrelevant alternatives assumption. This paper introduces a random utility maximization model of tour scheduling called the bivariate multinomial probit. This specification enables correlations across TOD alternatives, both outbound and return (on a tour) and over time slots (in a day). The model is estimated in a Bayesian setting on work-tour data from the San Francisco Bay Area with 30-minute time slots at most times of day (for both outbound and inbound journeys). Empirical results suggest that a variety of individual, household, and tour characteristics have reasonable effects on scheduling behavior. For instance, older persons typically pursue work tours at earlier times of day, part-time workers pursue their work tours later, and those with additional activities and tours tend to arrive slightly later and leave much earlier than those undertaking only a single tour, everything else constant. The model outperforms a comparable MNL, while offering reasonable implications under a variety of road-tolling scenarios." @default.
• W1988622014 created "2016-06-24" @default.
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• W1988622014 date "2012-08-01" @default.
• W1988622014 modified "2023-09-25" @default.
• W1988622014 title "A Bivariate Multinomial Probit Model for Trip Scheduling: Bayesian Analysis of the Work Tour" @default.
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• W1988622014 doi "https://doi.org/10.1287/trsc.1110.0397" @default.
• W1988622014 hasPublicationYear "2012" @default.
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