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Daily activity-travel scheduling behaviour of non-workers in the National Capital Region (NCR) of Canada

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  • Nurul Habib, Khandker
  • El-Assi, Wafic
  • Hasnine, Md. Sami
  • Lamers, James

Abstract

This paper uses household travel survey data (of the National Capital Region of Canada) and a comprehensive random utility maximizing travel options modelling approach to investigate non-workers’ activity-travel scheduling behaviour. The empirical model reveals that the presence of children shapes the daily activity-travel patterns of non-workers by reducing the flexibility of out-of-home activity-type choices. Availability of private cars increases flexibility in travelling and increases the spread of spatial locations of out-of-home activities of non-workers. Income plays a significant role in non-workers’ activity-travel behaviour and it seems that non-workers from lower to middle-income households are less active (return home early) than those living in higher income households. In general, it is found that male non-workers are less active than the female non-workers and it is also evident that non-workers living in single detached houses are less active (return home early) than those living in condos/apartments. These findings have an implication to health issues as the average age of non-workers is over 50years and the majority of detached houses are far from the central business district.

Suggested Citation

  • Nurul Habib, Khandker & El-Assi, Wafic & Hasnine, Md. Sami & Lamers, James, 2017. "Daily activity-travel scheduling behaviour of non-workers in the National Capital Region (NCR) of Canada," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 1-16.
  • Handle: RePEc:eee:transa:v:97:y:2017:i:c:p:1-16
    DOI: 10.1016/j.tra.2017.01.003
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    References listed on IDEAS

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    1. Saleh, Wafaa & Farrell, Séona, 2005. "Implications of congestion charging for departure time choice: Work and non-work schedule flexibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 773-791.
    2. Kim, Seung-Nam & Choo, Sangho & Mokhtarian, Patricia L., 2015. "Home-based telecommuting and intra-household interactions in work and non-work travel: A seemingly unrelated censored regression approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 197-214.
    3. Etminani-Ghasrodashti, Roya & Ardeshiri, Mahyar, 2016. "The impacts of built environment on home-based work and non-work trips: An empirical study from Iran," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 196-207.
    4. Swait, Joffre, 2003. "Flexible Covariance Structures for Categorical Dependent Variables through Finite Mixtures of Generalized Extreme Value Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 80-87, January.
    5. Khandker Habib, 2011. "A random utility maximization (RUM) based dynamic activity scheduling model: Application in weekend activity scheduling," Transportation, Springer, vol. 38(1), pages 123-151, January.
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    Citations

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    Cited by:

    1. Manish Shirgaokar & Kelly Lanyi-Bennett, 2020. "I’ll have to drive there: How daily time constraints impact women’s car use differently than men’s," Transportation, Springer, vol. 47(3), pages 1365-1392, June.
    2. Md Sami Hasnine & Khandker Nurul Habib, 2020. "Modelling the dynamics between tour-based mode choices and tour-timing choices in daily activity scheduling," Transportation, Springer, vol. 47(5), pages 2635-2669, October.
    3. Usman Ahmed & Ana Tsui Moreno & Rolf Moeckel, 2021. "Microscopic activity sequence generation: a multiple correspondence analysis to explain travel behavior based on socio-demographic person attributes," Transportation, Springer, vol. 48(3), pages 1481-1502, June.
    4. Usman Ahmed & Ana Tsui Moreno & Rolf Moeckel, 0. "Microscopic activity sequence generation: a multiple correspondence analysis to explain travel behavior based on socio-demographic person attributes," Transportation, Springer, vol. 0, pages 1-22.
    5. Yangcheng Gu & Haruka Kato & Daisuke Matsushita, 2023. "Relationship between Health Status and Daily Activities Based on Housing Type among Suburban Residents during COVID-19 Self-Isolation," IJERPH, MDPI, vol. 20(3), pages 1-12, February.
    6. Hasnine, Md Sami & Habib, Khandker Nurul, 2018. "What about the dynamics in daily travel mode choices? A dynamic discrete choice approach for tour-based mode choice modelling," Transport Policy, Elsevier, vol. 71(C), pages 70-80.

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