Should we abandon activity type analysis? Redefining activities by their salient attributes
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
Volume (Year): 33 (2006)
Issue (Month): 6 (November)
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- Sean Doherty & Eric Miller, 2000. "A computerized household activity scheduling survey," Transportation, Springer, vol. 27(1), pages 75-97, February.
- 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.
- 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.
- 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.
- 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, 03.
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