'The University of Texas at Austin, Bureau of Economic Geology'
Abstract
At the time of publication M.M Hoklas, S.K. Dubey, and C.R. Bhat were at the University of Texas at Austin. V.M Garikapati at Arizona State University, R.M. Pendyala at Georgia Institute of Technology, and D. Hyun You at Arizona State University.The health and well-being of individuals is related to their activity-travel patterns. Individuals
who undertake physically active episodes such as walking and bicycling are likely to have
improved health outcomes compared to individuals with sedentary auto-centric lifestyles.
Activity-based travel demand models are able to predict activity-travel patterns of individuals at
a high degree of fidelity, thus providing rich information for transportation and public health
professionals to infer health outcomes that may be experienced by individuals in various
geographic and demographic market segments. However, models of activity-travel demand do
not account for the attitudinal factors and lifestyle preferences that affect activity-travel and
mode use patterns. Such attitude and preference variables are virtually never collected explicitly
in travel surveys, rendering it difficult to include them in model specifications. This paper
applies Bhat’s (2014) Generalized Heterogeneous Data Model (GHDM) approach, whereby
latent constructs representing the degree to which individuals are health conscious and inclined
to pursue physical activities may be modeled as a function of observed socio-economic and
demographic variables and then included as explanatory factors in models of activity-travel
outcomes and walk and bicycle use. The model system is estimated on the 2005-2006 National
Health and Nutrition Examination Survey (NHANES) sample, demonstrating the efficacy of the
approach and the importance of including such latent constructs in model specifications that
purport to forecast activity and time use patterns.Civil, Architectural, and Environmental Engineerin