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A comparison of the personal and neighborhood characteristics associated with ridesourcing, transit use, and driving with NHTS data

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  • Deka, Devajyoti
  • Fei, Da

Abstract

The opportunity to conduct an overarching national study to examine the characteristics of ridesourcing users and their neighborhoods was absent until the 2017 National Household Travel Survey (NHTS) dataset was released in 2018. As the 2017 NHTS combines ridesourcing with taxi and limo in the trip file, ridesourcing trip characteristics cannot be separately analyzed. Thus, the paper examines the characteristics of users and neighborhoods associated with ridesourcing trip frequency from the person file, defined as the number of rides taken in 30 days. Because the public-use NHTS dataset includes only limited information about the neighborhoods where the respondents live, additional data from the NHTS DOT files were analyzed so that the characteristics of the neighborhoods could be fully comprehended. In an effort to examine the proximity of those neighborhoods to public transit stations and stops, GIS data on transit stations and stops were analyzed from the Bureau of Transportation Statistics and the US Department of Homeland Security. A zero-inflated negative binomial (ZINB) model was used to identify the variables associated with ridesourcing trip frequency. Two similar models were used to identify the variables associated with public transit trip frequency and annual vehicle miles driven. The analysis showed that the direction of the effects of the personal and neighborhood characteristics on ridesourcing and transit trip frequency is mostly similar, but often dissimilar to their effects on miles driven. A significant finding of this research is that people living near transit stations/stops use ridesourcing more frequently.

Suggested Citation

  • Deka, Devajyoti & Fei, Da, 2019. "A comparison of the personal and neighborhood characteristics associated with ridesourcing, transit use, and driving with NHTS data," Journal of Transport Geography, Elsevier, vol. 76(C), pages 24-33.
    • Handle: RePEc:eee:jotrge:v:76:y:2019:i:c:p:24-33
    DOI: 10.1016/j.jtrangeo.2019.03.001
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    References listed on IDEAS

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    Cited by:

    1. Barajas, Jesus & Brown, Anne, 2020. "Not Minding the Gap: Does Ride-Hailing Serve Transit Deserts?," SocArXiv y4jwk, Center for Open Science.
    2. Behram Wali & Paolo Santi & Carlo Ratti, 2023. "A joint demand modeling framework for ride-sourcing and dynamic ridesharing services: a geo-additive Markov random field based heterogeneous copula framework," Transportation, Springer, vol. 50(5), pages 1809-1845, October.
    3. Bi, Hui & Ye, Zhirui & Hu, Liyang & Zhu, He, 2021. "Why they don't choose bus service? Understanding special online car-hailing behavior near bus stops," Transport Policy, Elsevier, vol. 114(C), pages 280-297.
    4. Qiao, Si & Yeh, Anthony Gar-On, 2021. "Is ride-hailing a valuable means of transport in newly developed areas under TOD-oriented urbanization in China? Evidence from Chengdu City," Journal of Transport Geography, Elsevier, vol. 96(C).
    5. Dean, Matthew D. & Kockelman, Kara M., 2021. "Spatial variation in shared ride-hail trip demand and factors contributing to sharing: Lessons from Chicago," Journal of Transport Geography, Elsevier, vol. 91(C).
    6. Wang, Kaili & Liu, Yicong & Mashrur, Sk Md & Loa, Patrick & Habib, Khandker Nurul, 2021. "COVid-19 influenced households’ Interrupted Travel Schedules (COVHITS) survey: Lessons from the fall 2020 cycle," Transport Policy, Elsevier, vol. 112(C), pages 43-62.
    7. Qiao, Si & Zhang, Mengzhu & Yeh, Anthony Gar-On, 2023. "Mind the gender gap in ride-hailing from the demand side," Journal of Transport Geography, Elsevier, vol. 107(C).
    8. Guanwei Zhao & Zhitao Li & Yuzhen Shang & Muzhuang Yang, 2022. "How Does the Urban Built Environment Affect Online Car-Hailing Ridership Intensity among Different Scales?," IJERPH, MDPI, vol. 19(9), pages 1-25, April.
    9. Loa, Patrick & Nurul Habib, Khandker, 2021. "Examining the influence of attitudinal factors on the use of ride-hailing services in Toronto," Transportation Research Part A: Policy and Practice, Elsevier, vol. 146(C), pages 13-28.
    10. Edwards, Mickey, 2020. "Nonstandard ridehail use in Austin," Journal of Transport Geography, Elsevier, vol. 86(C).
    11. Zhang, Zhaolin & Zhai, Guocong & Xie, Kun & Xiao, Feng, 2022. "Exploring the nonlinear effects of ridesharing on public transit usage: A case study of San Diego," Journal of Transport Geography, Elsevier, vol. 104(C).
    12. Shirgaokar, Manish & Nobler, Erin, 2021. "Differences in daily trips between immigrants and US-born individuals: Implications for social integration," Transport Policy, Elsevier, vol. 105(C), pages 103-114.
    13. Barajas, Jesus M. & Brown, Anne, 2021. "Not minding the gap: Does ride-hailing serve transit deserts?," Journal of Transport Geography, Elsevier, vol. 90(C).
    14. Chalermpong, Saksith & Ratanawaraha, Apiwat & Anuchitchanchai, Ornicha, 2023. "Motorcycle taxis' varying degrees of complementarity and substitution with public transit in Bangkok," Journal of Transport Geography, Elsevier, vol. 108(C).
    15. Zou, Zhenpeng & Cirillo, Cinzia, 2021. "Does ridesourcing impact driving decisions: A survey weighted regression analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 146(C), pages 1-12.
    16. Elisa Borowski & Jason Soria & Joseph Schofer & Amanda Stathopoulos, 2020. "Disparities in ridesourcing demand for mobility resilience: A multilevel analysis of neighborhood effects in Chicago, Illinois," Papers 2010.15889, arXiv.org.
    17. Soltani, Ali & Allan, Andrew & Khalaj, Fahimeh & Pojani, Dorina & Mehdizadeh, Milad, 2021. "Ridesharing in Adelaide: Segmentation of users," Journal of Transport Geography, Elsevier, vol. 92(C).
    18. Loa, Patrick & Ong, Felita & Hawkins, Jason & Nurul Habib, Khandker, 2023. "Unravelling the relationship between ride-sourcing services and conventional modes in the city of Toronto: A stated preference study," Transport Policy, Elsevier, vol. 141(C), pages 209-220.
    19. Chang, Hung-Hao & Lee, Brian & Yang, Feng-An & Liou, Yu-You, 2021. "Does COVID-19 affect metro use in Taipei?," Journal of Transport Geography, Elsevier, vol. 91(C).
    20. Loa, Patrick & Hossain, Sanjana & Liu, Yicong & Nurul Habib, Khandker, 2022. "How has the COVID-19 pandemic affected the use of ride-sourcing services? An empirical evidence-based investigation for the Greater Toronto Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 46-62.
    21. Muhamad Rizki & Tri Basuki Joewono & Dimas Bayu Endrayana Dharmowijoyo & Dwi Prasetyanto, 2021. "The Effects of On- and Before- Journey Advantages Using Ride-Sourcing in Indonesia," Sustainability, MDPI, vol. 13(19), pages 1-20, October.
    22. Ghazaleh Azimi & Alireza Rahimi & Xia Jin, 2022. "Exploring the attitudes of Millennials and Generation Xers toward ridesourcing services," Transportation, Springer, vol. 49(6), pages 1765-1799, December.

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