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Millennials, built form, and travel insights from a nationwide typology of U.S. neighborhoods

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  • Ralph, Kelcie
  • Voulgaris, Carole Turley
  • Taylor, Brian D.
  • Blumenberg, Evelyn
  • Brown, Anne E.

Abstract

We examine the relationship between the built environment and the travel of Millennials in the United States. We develop a neighborhood typology to characterize the built environment and transportation networks in almost every U.S. census tract, allowing us to identify possible synergistic and/or threshold effects on travel. We measure travel behavior in two ways: (1) using a multi-faceted traveler typology created using latent class analysis, and (2) by measuring the vehicle miles of travel among people in each of these traveler types. This dual approach allows us to distinguish between the built environment changes needed to encourage travel by modes other than driving, and those needed to reduce vehicle miles traveled among drivers. Using a multinomial logistic regression, we find that travel patterns are relatively stable along much of the urban-rural continuum, everything else equal. Driving was substantially lower only in “Old Urban” neighborhoods, where densities, job access, and transit service are dramatically higher than in all other neighborhood types. This finding implies that dramatic changes in the built environment—doubling or even tripling development density or transit service—may do little to get young people out of their cars when initial densities or transit services are low, as they are in most of the U.S. Conversely, reducing vehicle miles traveled among drivers appears to require more modest built form changes, a finding that offers some room for optimism among those concerned with auto dependence.

Suggested Citation

  • Ralph, Kelcie & Voulgaris, Carole Turley & Taylor, Brian D. & Blumenberg, Evelyn & Brown, Anne E., 2016. "Millennials, built form, and travel insights from a nationwide typology of U.S. neighborhoods," Journal of Transport Geography, Elsevier, vol. 57(C), pages 218-226.
  • Handle: RePEc:eee:jotrge:v:57:y:2016:i:c:p:218-226
    DOI: 10.1016/j.jtrangeo.2016.10.007
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    References listed on IDEAS

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    Cited by:

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    4. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    5. Delbosc, Alexa & Naznin, Farhana, 2019. "Future life course and mobility: A latent class analysis of young adults in Victoria, Australia," Transport Policy, Elsevier, vol. 77(C), pages 104-116.
    6. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Comparisons of observed and unobserved parameter heterogeneity in modeling vehicle-miles driven," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    7. Michał Suchanek & Agnieszka Szmelter-Jarosz, 2019. "Environmental Aspects of Generation Y’s Sustainable Mobility," Sustainability, MDPI, vol. 11(11), pages 1-13, June.
    8. Choi, Yunkyung & Guhathakurta, Subhrajit, 2024. "Unraveling the diversity in transit-oriented development," Transportation Research Part A: Policy and Practice, Elsevier, vol. 182(C).
    9. Xize Wang, 2022. "Has the Relationship between Urban and Suburban Automobile Travel Changed across Generations? Comparing Millennials and Generation Xers in the United States," Papers 2206.10601, arXiv.org.
    10. Nash, Sean & Mitra, Raktim, 2019. "University students' transportation patterns, and the role of neighbourhood types and attitudes," Journal of Transport Geography, Elsevier, vol. 76(C), pages 200-211.
    11. Delbosc, Alexa & McCarthy, Laura, 2021. "Pushed back, pulled forward: Exploring the impact of COVID-19 on young adults’ life plans and future mobility," Transport Policy, Elsevier, vol. 107(C), pages 43-51.
    12. Wang, Xize, 2019. "Has the Relationship between Urban and Suburban Automobile Travel Changed across Generations? Comparing Millennials and Generation Xers in the United States," SocArXiv 2y5vj, Center for Open Science.

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