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An integrated analysis of workers’ physically active activity and active travel choice behavior

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  • Sener, Ipek N.
  • Reeder, Phillip R.

Abstract

Using Texas add-on sample data from the 2009 National Household Travel Survey, this study examines adult workers’ daily active choice decisions in the context of physical activity and attendant health benefits. The study looked at workers’ two choice behaviors: active activity and active travel. The first choice behavior, active activity, is developed as an ordered-response model based on the number of physically active recreational activities pursued during the workday. The second choice behavior, active travel, is developed as a binary-response model that examines workers’ active travel choices—whether or not the worker used any active mode of travel during the same workday. The study improves the understanding and knowledge of observed factors influencing workers’ physically active activity-travel behavior. The study also provides several observations regarding the role (and constraints) of employment in individuals’ active choices. Using a flexible copula modeling methodology, we explore the true correlation (or dependence) between the two behavior choices that could occur due to the presence of unobserved factors, suggesting a simultaneously low or simultaneously high propensity for being physically active across workers. The study findings suggest that transportation and public health policy makers can mutually benefit from encouraging workers to be physically active (from an activity and/or travel perspective). Overall, the study draws attention to the integrated nature of the public health and transportation fields, thereby providing a distinct view of active/inactive choice behavior. To our knowledge, this is the first study exploring a rich variety of components for workers’ active activity-travel behavior through a robust copula approach.

Suggested Citation

  • Sener, Ipek N. & Reeder, Phillip R., 2014. "An integrated analysis of workers’ physically active activity and active travel choice behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 381-393.
    • Handle: RePEc:eee:transa:v:67:y:2014:i:c:p:381-393
    DOI: 10.1016/j.tra.2014.03.007
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    References listed on IDEAS

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    1. Saelens, B.E. & Sallis, J.F. & Black, J.B. & Chen, D., 2003. "Neighborhood-Based Differences in Physical Activity: An Environment Scale Evaluation," American Journal of Public Health, American Public Health Association, vol. 93(9), pages 1552-1558.
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    6. Bhat, Chandra R. & Eluru, Naveen, 2009. "A copula-based approach to accommodate residential self-selection effects in travel behavior modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 749-765, August.
    7. Chandra Bhat & Ipek Sener, 2009. "A copula-based closed-form binary logit choice model for accommodating spatial correlation across observational units," Journal of Geographical Systems, Springer, vol. 11(3), pages 243-272, September.
    8. Bhat, Chandra & Lockwood, Allison, 2004. "On distinguishing between physically active and physically passive episodes and between travel and activity episodes: an analysis of weekend recreational participation in the San Francisco Bay area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(8), pages 573-592, October.
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    Cited by:

    1. Wöhner, Fabienne, 2023. "Work flexibly, travel more healthily? How telework and flextime affect active travel in Switzerland," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    2. Lee, Richard J. & Sener, Ipek N., 2016. "Transportation planning and quality of life: Where do they intersect?," Transport Policy, Elsevier, vol. 48(C), pages 146-155.
    3. Julio César dos Santos & Paulo Ribeiro & Ricardo Jorge Silva Bento, 2023. "A Review of the Promotion of Sustainable Mobility of Workers by Industries," Sustainability, MDPI, vol. 15(11), pages 1-18, May.

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