2005
DOI: 10.1016/j.trb.2004.04.002
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A multidimensional mixed ordered-response model for analyzing weekend activity participation

Abstract: The objective of this paper is to examine the frequency of participation of individuals in out-of-home non-work and non-school episodes over the weekend. A multivariate mixed ordered response formulation accommodating the effects of explanatory variables and capturing the dependence among the propensity to participate in different activity types is presented and applied using a San Francisco Bay area travel survey conducted in 2000. The results indicate the important effects of household sociodemographics (inc… Show more

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Cited by 102 publications
(58 citation statements)
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“…Instead, regarding physical activities, Bhat and Srinivasan [48] examined the land use effect on weekend out-of-home activities. They found that land use variables are insignificant altogether and suspected that the insignificance could be explained by RSS.…”
Section: Relationship Of Land Use With Total Travel Measures On Weekdmentioning
confidence: 99%
“…Instead, regarding physical activities, Bhat and Srinivasan [48] examined the land use effect on weekend out-of-home activities. They found that land use variables are insignificant altogether and suspected that the insignificance could be explained by RSS.…”
Section: Relationship Of Land Use With Total Travel Measures On Weekdmentioning
confidence: 99%
“…A problem with this approach, however, is that the number of composite alternatives explodes with the number of elemental alternatives. Another approach is to use the multivariate probit (logit) methods of Manchanda et al (1999), Baltas (2004), Edwards and Allenby (2003), and Bhat and Srinivasan (2005). But this approach is not based on a rigorous underlying utility-maximizing framework of multiple discreteness; rather, it represents a statistical "stitching" of univariate utility maximizing models.…”
Section: Introductionmentioning
confidence: 99%
“…Another approach to analyze multiple discrete situations is to use the multivariate probit (logit) methods of Manchanda et al (1999), Baltas (2004), Edwards and Allenby (2003), and Bhat and Srinivasan (2005). In these multivariate methods, the multiple discreteness is handled through statistical methods that generate correlation between univariate utility maximizing models for single discreteness.…”
Section: Introductionmentioning
confidence: 99%