An Analysis of Weekly Out-of-Home Discretionary Activity Participation and Time-Use Behavior
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Activity-travel behavior research has hitherto focused on the modeling and understanding of daily time use and activity patterns and resulting travel demand. In this particular paper, an analysis and modeling of weekly activity-travel behavior is presented using a unique multi-week activity-travel behavior data set collected in and around Zurich, Switzerland. The paper focuses on six categories of discretionary activity participation to understand the determinants of, and the inter-personal and intra-personal variability in, weekly activity engagement at a detailed level. A panel version of the Mixed Multiple Discrete Continuous Extreme Value model (MMDCEV) that explicitly accounts for the panel (or repeated-observations) nature of the multi-week activity-travel behavior data set is developed and estimated on the data set. The model also controls for individual-level unobserved factors that lead to correlations in activity engagement preferences across different activity types. To our knowledge, this is the first formulation and application of a panel MMDCEV structure in the econometric literature. The analysis suggests the high prevalence of intra-personal variability in discretionary activity engagement over a multi-week period along with inter-personal variability that is typically considered in activitytravel modeling. In addition, the panel MMDCEV model helped identify the observed socioeconomic factors and unobserved individual specific factors that contribute to variability in multi-week discretionary activity participation.
At the time of publication E. Spissu and C.R. Bhat were at the University of Texas at Austin; A.R. Pinjari was at the University of South Florida; R.M. Pendyala was at Arizona State University; and K.W. Axhausen was at ETH Zurich.