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Innovations in Travel Demand Modeling, Volume 2: Papers (2008)

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Suggested Citation:"T57054 txt_130.pdf." National Academies of Sciences, Engineering, and Medicine. 2008. Innovations in Travel Demand Modeling, Volume 2: Papers. Washington, DC: The National Academies Press. doi: 10.17226/13678.
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7. The popularity of modeling travel during week- ends and for special events reinforces the need to accom- modate joint activity and travel patterns in travel models. Recent years have seen increasing efforts in the field of transportation engineering on studying interpersonal interactions in activity–travel patterns. These studies may be classified into two categories. The first category adopts econometric modeling methods to relate joint activity–travel choices with characteristics of the deci- sion makers (see Srinivasan and Bhat 2006). Most of these studies use data from conventional travel surveys but very few have examined individuals’ interactions with nonhousehold members. The second category is largely focused on the concept of social networks and seeks to explore the nature and extent of individuals’ social interactions (see Arentze and Timmermans 2006). Thus, this latter group of studies is not restricted to ana- lyzing within- household interactions. Despite this increasing interest, our empirical knowl- edge of individuals’ interactions with nonhousehold members is limited, largely because conventional house- hold–travel surveys (which form the basis of activ- ity–travel modeling) typically do not collect this data. An exception is the recent CentreSIM travel survey (Goulias and Kim 2005), which included an open- ended question, “with whom was this activity episode undertaken,” to collect data from about 1,400 individuals on the types of companions with whom each activity was undertaken. The first analysis results indicate that approximately one- third of activity–travel episodes and daily time is spent alone and a significant fraction of joint episodes are pursued with non household members (both relatives and nonrelatives). The goal of this study is to contribute to the under- standing of activities and travel pursued by individuals jointly with household and nonhousehold members. Toward that end, there are two major tasks. First, an analysis is undertaken to determine the extent to which each activity type is pursued jointly. Further, this analysis aims to illustrate the differences in the companion- type choices (household versus nonhousehold members) across the activity types. The next task is focused on leisure activities. The motivation for this focus is that, among all activity types, the desire for companionship for leisure is likely to be highest. Specifically, models are developed to examine the impacts of demographic char- acteristics, day of the week, and activity episode dura- tions on the choice of companion type. The rest of this paper is organized as follows. The sec- tion immediately below describes the data used in this analysis. The empirical results are presented in the sec- tion that follows. The final section provides a summary and highlights the insights from this study. DATA DESCRIPTION This study uses data from the American Time Use Survey (ATUS). Conducted by the Census Bureau under contract with the Bureau of Labor Statistics, ATUS collects detailed individual- level daily time use information. The sample is drawn from a subset of households responding to the Current Population Survey interviews. One indi- vidual aged 15 years or older is selected from each house- hold for the survey. Data collection began in January 2003. Currently, data samples collected in 2003 (412,611 activity episodes from 20,000 individuals) and 2004 (279,042 activity episodes from 13,973 individuals) are available. Additional details can be obtained from the ATUS website, http://www.bls.gov/tus/home.htm. The ATUS data are attractive for our analysis for sev- eral reasons. First, the data sample is large (34,693 per- sons surveyed over 2 years) and represents the nation as a whole as opposed to a specific geographic area. Second, the survey obtained information on all persons (both household and nonhousehold members) accompanying the respondent for each activity episode. The companions were classified using the scheme presented in Table 1. Third, the survey used a disaggregate three- tier activity classification scheme thereby facilitating the analysis joint activity participation at a fine resolution of activity types. It is also necessary to point out that an issue with using ATUS for analyzing joint activity participation decisions is the absence of time use information for the respondents’ companion(s). ATUS collects time use data only for one person per household. Therefore, the complete activity participation decisions of even the respondents’ own household members are unknown. Consequently, it is not 130 INNOVATIONS IN TRAVEL DEMAND MODELING, VOLUME 2 TABLE 1 Companion-Type Classification Scheme Adopted in ATUS Household Members Spouse (husband/wife) Unmarried partner Own household child Grandchild Parent (father/mother) Brother/sister Other related person (aunt, cousin, nephew) Foster child Housemate/roommate Roomer/boarder Other nonrelative Nonhousehold Members Own nonhousehold child Parents or parents-in-law (not living in household) Other nonhousehold family members (age <18) Other nonhousehold family members (age ≥18) Friends Co-workers/colleagues/clients Neighbors/acquaintances Other nonhousehold children (age <18) Other nonhousehold adults (age ≥18)

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TRB Conference Proceedings 42, Innovations in Travel Demand Modeling, Volume 2: Papers includes the papers that were presented at a May 21-23, 2006, conference that examined advances in travel demand modeling, explored the opportunities and the challenges associated with the implementation of advanced travel models, and reviewed the skills and training necessary to apply new modeling techniques. TRB Conference Proceedings 42, Innovations in Travel Demand Modeling, Volume 1: Session Summaries is available online.

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