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Multivariate analysis of trip-chaining behavior

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  • John V. Thomas
  • Robert Noland

Abstract

Trip-chaining behavior has generally been associated with various demographic characteristics of households and individuals. This includes households with children having more complex activity patterns, or those who are employed needing to conduct activities on the way to and from work because of time constraints. No studies, as yet, have controlled for other factors that might influence trip chaining behaviour, such as levels of urbanization, public transport availability, use of other transport modes, or various other local environmental factors. This paper explores these issues using both the 1995 Nationwide Personal Transportation Survey and the 2001 National Household Travel Survey. Both surveys have data on trip chaining behavior that allows multivariate analysis of individual level behavior. Various choice models are estimated, including ordered models that account for the number of chains in a trip. Results for both the 1995 and 2001 surveys are presented to examine potential changes in behavior over time.

Suggested Citation

  • John V. Thomas & Robert Noland, 2005. "Multivariate analysis of trip-chaining behavior," ERSA conference papers ersa05p541, European Regional Science Association.
    • Handle: RePEc:wiw:wiwrsa:ersa05p541
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    References listed on IDEAS

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    Cited by:

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    3. Bautista-Hernández, Dorian Antonio, 2022. "Individual, household, and urban form determinants of trip chaining of non-work travel in México City," Journal of Transport Geography, Elsevier, vol. 98(C).
    4. Tufayel Chowdhury & Darren M. Scott, 2020. "Role of the built environment on trip-chaining behavior: an investigation of workers and non-workers in Halifax, Nova Scotia," Transportation, Springer, vol. 47(2), pages 737-761, April.
    5. Steven R. Gehrke & Timothy F. Welch, 2017. "The built environment determinants of activity participation and walking near the workplace," Transportation, Springer, vol. 44(5), pages 941-956, September.
    6. Ta, Na & Zhao, Ying & Chai, Yanwei, 2016. "Built environment, peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data," Journal of Transport Geography, Elsevier, vol. 57(C), pages 161-170.
    7. Naznin Sultana Daisy & Lei Liu & Hugh Millward, 2020. "Trip chaining propensity and tour mode choice of out-of-home workers: evidence from a mid-sized Canadian city," Transportation, Springer, vol. 47(2), pages 763-792, April.
    8. Wang, Rui, 2015. "The stops made by commuters: evidence from the 2009 US National Household Travel Survey," Journal of Transport Geography, Elsevier, vol. 47(C), pages 109-118.
    9. Yang, Dujuan & Timmermans, Harry & Grigolon, Anna, 2013. "Exploring heterogeneity in travel time expenditure of aging populations in the Netherlands: results of a CHAID analysis," Journal of Transport Geography, Elsevier, vol. 33(C), pages 170-179.
    10. João De Abreu e Silva, 2018. "The Effects of Land-Use Patterns on Home-Based Tour Complexity and Total Distances Traveled: A Path Analysis," Sustainability, MDPI, vol. 10(3), pages 1-16, March.
    11. Jan-Dirk Schmöcker & Fengming Su & Robert Noland, 2010. "An analysis of trip chaining among older London residents," Transportation, Springer, vol. 37(1), pages 105-123, January.
    12. Michael Duncan, 2016. "How much can trip chaining reduce VMT? A simplified method," Transportation, Springer, vol. 43(4), pages 643-659, July.
    13. Rafiq, Rezwana & McNally, Michael G., 2022. "A structural analysis of the work tour behavior of transit commuters," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 61-79.
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    15. Henly, Megan & Brucker, Debra L., 2019. "Transportation patterns demonstrate inequalities in community participation for working-age Americans with disabilities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 93-106.

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