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Exploring day-to-day variability in time use for household members

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  • Kang, Hejun
  • Scott, Darren M.
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    Abstract

    Studies of activity-travel patterns typically use 1-day or pooled samples, and more often than not, are conducted at the individual level. By default, they assume that activity-travel decisions are uniform from 1 day to the next and individuals are independent from one another. Such assumptions do not reflect reality. This research investigates day-to-day variability in activity time-use patterns of household members while incorporating variations in their interactions. Results from a descriptive analysis and a series of daily structural equation models provide evidence of day-to-day variability in activity time-use patterns. Specifically, time-use patterns on weekdays are substantially different from those on weekends. Furthermore, compared to independent activities, there is a higher proportion of intra-personal variability and a lower proportion of inter-personal variability for joint activities. These findings suggest that transportation planners should not combine independent and joint activities as has been the case in the recent past, nor should they use single-day or pooled models when estimating activity time-use patterns.

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    Bibliographic Info

    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 44 (2010)
    Issue (Month): 8 (October)
    Pages: 609-619

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    Handle: RePEc:eee:transa:v:44:y:2010:i:8:p:609-619

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    Related research

    Keywords: Activity analysis Intra-household interactions Joint activities Time use Toronto Travel-Activity Panel Survey Variability analysis;

    References

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    17. Bhat, Chandra R. & Frusti, Teresa & Zhao, Huimin & Schönfelder, Stefan & Axhausen, Kay W., 2004. "Intershopping duration: an analysis using multiweek data," Transportation Research Part B: Methodological, Elsevier, vol. 38(1), pages 39-60, January.
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    Cited by:
    1. Wilson, Jeffrey & Spinney, Jamie & Millward, Hugh & Scott, Darren & Hayden, Anders & Tyedmers, Peter, 2013. "Blame the exurbs, not the suburbs: Exploring the distribution of greenhouse gas emissions within a city region," Energy Policy, Elsevier, vol. 62(C), pages 1329-1335.
    2. Walker, Joan L. & Ehlers, Emily & Banerjee, Ipsita & Dugundji, Elenna R., 2011. "Correcting for endogeneity in behavioral choice models with social influence variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 362-374, May.
    3. Yu Liu & Chaogui Kang & Song Gao & Yu Xiao & Yuan Tian, 2012. "Understanding intra-urban trip patterns from taxi trajectory data," Journal of Geographical Systems, Springer, vol. 14(4), pages 463-483, October.
    4. Sharmeen, Fariya & Arentze, Theo & Timmermans, Harry, 2014. "An analysis of the dynamics of activity and travel needs in response to social network evolution and life-cycle events: A structural equation model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 159-171.

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