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Companionship for Leisure Activities An Empirical Analysis Using the American Time Use Survey Sivaramakrishnan Srinivasan, University of Florida Chandra R. Bhat, University of Texas at Austin T he activity-based travelmodeling paradigm recog- patterns of persons not directly impacted by the policy. nizes that individuals undertake activity and travel These secondary impacts cannot be captured by models not only independently but also together with other that do not accommodate interpersonal interactions household and nonhousehold members. It has also been (Srinivasan and Bhat 2006). argued that the desire for interaction with other people is an 3. Individuals may be willing to travel farther and important stimulus for activitytravel generation and pursue activities for longer durations when the activity therefore warrants treatment in traveldemand models. or travel is being pursued with family or friends. Further, However, Axhausen (2005) notes that this important social such joint activity could be restricted to certain periods dimension of activitytravel behavior is not accommodated of the day. For example, Kemperman et al. (2006) iden- in travel modeling. Further, the modeling of interpersonal tify three peak periods for social activity participation interdependencies in activitytravel patterns is necessary for using data from The Netherlands. The timing and dura- realistic forecasts of travel patterns under alternate socioe- tions of trips and stops have substantial implications for conomictechnological scenarios and due to changes in determining the impacts of mobile-source (i.e., from land use and transportation system characteristics. The fol- vehicles) emissions on air quality. lowing examples serve to illustrate this point: 4. When individuals participate in activities with non- household members, they may also undertake travel to 1. Vehicle occupancy levels are determined by indi- pick up and drop off their companions. Such additional viduals' decisions to travel together, which are motivated travel cannot be effectively captured by individual-level by the desire to participate in the destination activity models. jointly. Thus, the modeling of joint activitytravel pur- 5. Social activities are perhaps not as flexible as they suits is necessary to determine the volume of vehicular have been treated traditionally (Kemperman et al. 2006). travel in the system, and consequently for the evaluation For example, some of the joint leisure activities pursued of policies such as HOV/HOT lanes (Vovsha et al. 2003). with nonhousehold members could be at the residence of Similarly, the individuals' response to carpooling incen- friends or family. Consequently, the destination choice tives depends on their ability to synchronize their travel for such travel may have limited sensitivity to the trans- patterns with those of others. portation system characteristics (see also Carrasco et al. 2. Though participation in leisure activities is con- 2006). strained by individuals' obligations (Gliebe and Koppel- 6. The increasing adoption of ICTs (information and man 2002; Srinivasan and Bhat 2006), employer-based communication technologies) like cell phones, Internet, demand management strategies (such as flextime and and e-mail can have strong impacts on the social lifestyles telecommuting) could lead to increased leisure time and of people and hence on activities pursued with family and likelihood of joint activities, as well as alter the travel nonfamily members (Carrasco and Miller 2006). 129