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Can the built environment influence nonwork activity participation? An analysis with national data

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Abstract

Most of the research on the influence of the built environment on travel has focused on reducing the impacts of travel, but one of the primary benefits of travel is the opportunity to engage in activities. This study examines a national travel data set to see if variation in the built environment can facilitate participation in out-of-the-home, nonwork activities for households. Although several studies have examined the relationship between the built environment and nonwork trip generation in the past, none have looked at such a wide range of built environments as a national data set can provide. Built environment variables are associated with higher than expected impacts on household participation in nonwork activities, increasing or decreasing activity levels in the range of 8–47 %, depending largely upon the level of household vehicle ownership. For households without vehicles, high residential and employment densities appear to support greater nonwork activity. Households with full access to vehicles appear to be supported by higher than average residential and employment densities and mid-range urban and metropolitan area sizes. Interestingly, activity participation in households with limited vehicle access is for the most part not affected by the built environment in a statistically significant way. In sum, these results suggest that the built environment may play a larger role in facilitating activity participation than previously presumed.

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Notes

  1. I imputed income using ordered logistic regression, regressing income category against number of vehicles owned, number of workers in the household, home ownership, housing unit type, life cycle stage, and urban area size.

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Acknowledgments

Thanks to Noreen McDonald and Daniel Rodriguez for detailed and insightful comments on an earlier version of this article. Thanks to my dissertation advisor, Yan Song, for continuous advice and support. Many thanks also to Qi Zhen and Professor Steve Marron for the idea of using cross-validation and insights on how to compare different model formulas. Also I appreciate the advice of Nikhil Kaza on how to approach the statistical analysis. Also, I have much gratitude to the Royster Society, without whose financial support I would not have been able to embark upon this research.

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  1. Taubman College of Architecture and Urban Planning, University of Michigan, 2000 Bonisteel Blvd, Ann Arbor, MI, 48109-2069, USA

    Louis A. Merlin

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  1. Louis A. Merlin
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Correspondence to Louis A. Merlin.

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Merlin, L.A. Can the built environment influence nonwork activity participation? An analysis with national data. Transportation 42, 369–387 (2015). https://doi.org/10.1007/s11116-014-9554-1

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