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Should we abandon activity type analysis? Redefining activities by their salient attributes

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  • Sean Doherty

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Abstract

This paper poses a challenge and begins a search. The challenge is to reconsider the usefulness of traditional activity types (“work”, “shopping”, etc.) in the understanding and modelling of travel behaviour. The search is for the more salient attributes of activities that may serve to better explain complex travel behaviours—such as activity scheduling and tour formation. In particular, this paper focuses on explicit measures of the spatial, temporal and interpersonal flexibility of activities, along with several traditional attributes (frequency, duration, involved persons, travel time, and location). Data from a recent in-depth week-long activity scheduling survey was used to define and compare these attributes. Results show that considerable variability in the attributes between and within traditional activity groups is evident. This casts considerable uncertainty on assumptions that statically assign levels of spatial, temporal, and interpersonal flexibility to any given activity type. A Principal Components Analysis further revealed eight new distinct clusters of activities that share like attributes. The relative role of each attribute in each component is examined, and subjective interpretations emerged (e.g., “Long and frequent”, “Space and time flexible” “Social networking”). The implications of these results for future model development and research are discussed. Future research should continue to expand the search for salient attributes and link them more directly to decision processes. Copyright Springer Science+Business Media B.V. 2006

Suggested Citation

  • Sean Doherty, 2006. "Should we abandon activity type analysis? Redefining activities by their salient attributes," Transportation, Springer, vol. 33(6), pages 517-536, November.
    • Handle: RePEc:kap:transp:v:33:y:2006:i:6:p:517-536
    DOI: 10.1007/s11116-006-0001-9
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    File URL: http://hdl.handle.net/10.1007/s11116-006-0001-9
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    References listed on IDEAS

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    1. Ryuichi Kitamura & Cynthia Chen & Ram Pendyala & Ravi Narayanan, 2000. "Micro-simulation of daily activity-travel patterns for travel demand forecasting," Transportation, Springer, vol. 27(1), pages 25-51, February.
    2. Tim Schwanen & Martin Dijst, 2003. "Time windows in workers' activity patterns: Empirical evidence from the Netherlands," Transportation, Springer, vol. 30(3), pages 261-283, August.
    3. Bowman, J. L. & Ben-Akiva, M. E., 2001. "Activity-based disaggregate travel demand model system with activity schedules," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 1-28, January.
    4. Sean Doherty & Eric Miller, 2000. "A computerized household activity scheduling survey," Transportation, Springer, vol. 27(1), pages 75-97, February.
    5. T. Limanond & D.A. Niemeier & P.L. Mokhtarian, 2005. "Specification of a tour-based neighborhood shopping model," Transportation, Springer, vol. 32(2), pages 105-134, March.
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    Cited by:

    1. Linda Nijland & Theo Arentze & Harry Timmermans, 2014. "Multi-day activity scheduling reactions to planned activities and future events in a dynamic model of activity-travel behavior," Journal of Geographical Systems, Springer, vol. 16(1), pages 71-87, January.
    2. Ruiz, Tomás & Habib, Khandker Nurul, 2016. "Scheduling decision styles on leisure and social activities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 304-317.
    3. Auld, Joshua & Mohammadian, Abolfazl (Kouros) & Doherty, Sean T., 2009. "Modeling activity conflict resolution strategies using scheduling process data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 386-400, May.
    4. Akar, Gulsah & Clifton, Kelly J. & Doherty, Sean T., 2012. "Redefining activity types: Who participates in which leisure activity?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1194-1204.
    5. Mattioli, Giulio & Anable, Jillian & Vrotsou, Katerina, 2016. "Car dependent practices: Findings from a sequence pattern mining study of UK time use data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 56-72.
    6. Christa Hubers & Tim Schwanen & Martin Dijst, 2008. "Ict And Temporal Fragmentation Of Activities: An Analytical Framework And Initial Empirical Findings," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 99(5), pages 528-546, December.

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