Models of residential and workplace location choice prevalent in the literature often assume that one choice dimension is exogenous to the other. But a broad and uniform assumption that one choice dimension is exogenous and influences the other may be too strong to use as the foundation for current behavioral research or applied policy analysis. This paper examines the interdependence of residence and workplace choices and develops a novel approach to modeling these choice dependencies. Two problems related to such joint modeling efforts are addressed. First, through a latent market segment modeling approach, the paper offers a methodology for accommodating different sequential decision-making processes that may be present in the population–for example, residential location may be chosen first and may influence workplace location for one segment and vice versa. Second, the modeling approach offers a means of overcoming the exploding choice set problem when attempting to model multidimensional choice phenomena. The overall aim of the work is to model the structure of the interdependency between the choices that a household makes about residence location and the workplace choices of the workers in the household in the context of an integrated activity location and travel forecasting framework. This paper presents a joint model of residence location and workplace using activity-based travel survey data collected in the Puget Sound region of Washington state in 1999, with novel adaptation of recent methods for incorporating latent market segmentation within discrete choice models.


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    Titel :

    Modeling Interdependence in Household Residence and Workplace Choices


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:
    Waddell, Paul (Autor:in) / Bhat, Chandra (Autor:in) / Eluru, Naveen (Autor:in) / Wang, Liming (Autor:in) / Pendyala, Ram M. (Autor:in)


    Erscheinungsdatum :

    2007-01-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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