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Use of repeated cross-sectional travel surveys for developing meta models of activity-travel scheduling processes

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Listed:
  • Sarah Salem

    (Cairo University)

  • Khandker M. Nurul Habib

    (University of Toronto)

Abstract

The paper presents an investigation of the temporal transferability of activity scheduling process models and a Meta model of activity scheduling processed by using repeated cross-sectional datasets. Three repeated cross-sectional household travel survey datasets collected in the greater Toronto and Hamilton Area in the years 2001, 2006, and 2011 are used for the investigation. A random utility maximization based dynamic activity scheduling model is utilized to develop activity-travel scheduling models for non-workers and workers separately. Individual year-specific models are compared to identify the temporal stability of the effects of different variables in the model. Results are used to define temporal evolution components in the Meta models. Estimated models are tested for temporal transferability. Different transferability measures are used to test the temporal transferability of cross-sectional year-specific and the Meta models. Results demonstrate an approach of effectively using multiple repeated cross-sectional datasets as pseudo panel data to develop Meta models to improve the temporal transferability of activity scheduling models.

Suggested Citation

  • Sarah Salem & Khandker M. Nurul Habib, 2019. "Use of repeated cross-sectional travel surveys for developing meta models of activity-travel scheduling processes," Transportation, Springer, vol. 46(2), pages 395-423, April.
    • Handle: RePEc:kap:transp:v:46:y:2019:i:2:d:10.1007_s11116-018-9954-8
    DOI: 10.1007/s11116-018-9954-8
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    References listed on IDEAS

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