A Multivariate Ordered Response Model System for Adults' Weekday Activity Episode Generation by Activity Purpose and Social Context

dc.creatorFerdous, Nazneenen
dc.creatorEluru, Naveenen
dc.creatorBhat, Chandra R.en
dc.creatorMeloni, Italoen
dc.date.accessioned2014-04-04T17:41:25Zen
dc.date.available2014-04-04T17:41:25Zen
dc.date.issued2010en
dc.descriptionAt the time of publication N. Ferdous, N. Eluru, and C.R. Bhat were at the University of Texas at Austin; and I. Meloni was at the University of Cagliari.en
dc.description.abstractThis paper proposes a multivariate ordered response system framework to model the interactions in non-work activity episode decisions across household and non-household members at the level of activity generation. Such interactions in activity decisions across household and non-household members are important to consider for accurate activity-travel pattern modeling and policy evaluation. The econometric challenge in estimating a multivariate ordered-response system with a large number of categories is that traditional classical and Bayesian simulation techniques become saddled with convergence problems and imprecision in estimates, and they are also extremely cumbersome if not impractical to implement. We address this estimation problem by resorting to the technique of composite marginal likelihood (CML), an emerging inference approach in the statistics field that is based on the classical frequentist approach, is very simple to estimate, is easy to implement regardless of the number of count outcomes to be modeled jointly, and requires no simulation machinery whatsoever. The empirical analysis in the paper uses data drawn from the 2007 American Time UseSurvey (ATUS) and provides important insights into the determinants of adults' weekday activity episode generation behavior. The results underscore the substantial linkages in the activity episode generation of adults based on activity purpose and accompaniment type. The extent of this linkage varies by individual demographics, household demographics, day of the week, and season of the year. The results also highlight the flexibility of the CML approach to specify and estimate behaviorally rich structures to analyze inter-individual interactions inactivity episode generation.en
dc.description.departmentCivil, Architectural, and Environmental Engineeringen
dc.identifier.citationFerdous, N., N. Eluru, C.R. Bhat, and I. Meloni (2010). A Multivariate Ordered Response Model System for Adults' Weekday Activity Episode Generation by Activity Purpose and Social Context.Transportation Research Part B, Vol. 44, No. 8-9, pp. 922-943.en
dc.identifier.issn0191-2615en
dc.identifier.urihttp://hdl.handle.net/2152/23805en
dc.language.isoenen
dc.publisherElsevieren
dc.source.urihttp://www.sciencedirect.com/science/journal/01912615en
dc.subjectComposite Marginal Likelihood (CML) approachen
dc.subjectsocial interactionsen
dc.subjectactivity-based modelingen
dc.subjectmultivariate ordered probit modelen
dc.subjectAmerican Time Use Survey (ATUS)en
dc.titleA Multivariate Ordered Response Model System for Adults' Weekday Activity Episode Generation by Activity Purpose and Social Contexten
dc.typeArticleen

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