An Econometric Multi-Dimensional Choice Model of Activity-Travel Behavior
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Recent evidence suggests that many activity-travel choices are inter-dependent with one another and hence inextricably linked in ways that need to be better understood to help inform the specification of activity-based travel model systems. Model systems in practice often sequentially link a series of choice dimensions into a deeply nested logit model where accessibility variables (logsum terms) from lower nests cascade up through the structure to the higher levels in the model structure. While these model systems are convenient from a practical standpoint, they ignore the potential jointness in choice-making processes and do not effectively and directly capture the effects of spatial land use and built environment characteristics on activity generation. In this paper, a unified model of activity type choice (generation), time of day choice, mode choice, destination choice, and time use allocation (duration) is formulated and estimated on a survey sample data set drawn from the 2000 San Francisco Bay Area Travel Survey (BATS). The model system constitutes a joint multiple discrete continuous extreme value (MDCEV) multinomial logit (MNL) model, in which all discrete choices, except for destination choice, and the continuous duration dimension are modeled using the MDCEV, and destination choice is modeled as a MNL (with sampling of alternatives) nested and therefore integrated with the MDCEV model component. The parameter estimates of the joint model offer behaviorally intuitive results that support the integrated treatment of these choice dimensions as a choice bundle. The potential applicability of the model system is demonstrated through a policy simulation example that shows how changes in travel cost and time variables lead to changes in out-of-home discretionary activity participation.
At the time of publication N. Eluru was at McGill University; A.R. Pinjari was at University of South Florida; R.M. Pendyala was at Arizona State University; and C.R. Bhat was at the University of Texas at Austin.