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How does the propensity of living near rail transit moderate the influence of rail transit on transit trip frequency in Xi'an?

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  • Huang, Xiaoyan
  • Cao, Xinyu (Jason)
  • Cao, Xiaoshu
  • Yin, Jiangbin

Abstract

Many cities have made massive investments on rail systems to substitute transit for driving. Some studies have considered the confounding effect of attitudes in the connections between rail transit and travel behavior. However, they often focused on the average effect of rail transit and assumed that individuals' responses to transit improvements do not vary by their tastes. Using the 2014 data from Xi'an in China, this study explores the interaction effect between metro transit (heavy rail) and the propensity (i.e., predicted probability) of living in neighborhoods with metro transit on transit use. The propensity is positively associated with commute by metro transit and bus. Further, individuals with a strong propensity use transit equivalently no matter whether they live near metro transit, but metro transit tends to promote transit commute for those with a weak propensity of living near metro transit. Overall, building a rail line helps enhance transit ridership. Planners should also consider the variation in responses by individuals with different tastes when using policies to shape urban travel.

Suggested Citation

  • Huang, Xiaoyan & Cao, Xinyu (Jason) & Cao, Xiaoshu & Yin, Jiangbin, 2016. "How does the propensity of living near rail transit moderate the influence of rail transit on transit trip frequency in Xi'an?," Journal of Transport Geography, Elsevier, vol. 54(C), pages 194-204.
  • Handle: RePEc:eee:jotrge:v:54:y:2016:i:c:p:194-204
    DOI: 10.1016/j.jtrangeo.2016.05.016
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    References listed on IDEAS

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    Cited by:

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    2. Cao, Xinyu Jason, 2019. "Examining the effect of the Hiawatha LRT on auto use in the Twin Cities," Transport Policy, Elsevier, vol. 81(C), pages 284-292.
    3. Bing Yan & Yuan Rong & Liying Yu & Yuting Huang, 2022. "A Hybrid Intuitionistic Fuzzy Group Decision Framework and Its Application in Urban Rail Transit System Selection," Mathematics, MDPI, vol. 10(12), pages 1-26, June.
    4. Phani Kumar, P. & Ravi Sekhar, Ch. & Parida, Manoranjan, 2018. "Residential dissonance in TOD neighborhoods," Journal of Transport Geography, Elsevier, vol. 72(C), pages 166-177.
    5. Donggen Wang & Tao Lin, 2019. "Built environment, travel behavior, and residential self-selection: a study based on panel data from Beijing, China," Transportation, Springer, vol. 46(1), pages 51-74, February.
    6. Kamruzzaman, Md. & Giles-Corti, Billie & De Vos, Jonas & Witlox, Frank & Shatu, Farjana & Turrell, Gavin, 2021. "The life and death of residential dissonants in transit-oriented development: A discrete time survival analysis," Journal of Transport Geography, Elsevier, vol. 90(C).
    7. Long, Fenjie & Zheng, Longfei & Song, Zhida, 2018. "High-speed rail and urban expansion: An empirical study using a time series of nighttime light satellite data in China," Journal of Transport Geography, Elsevier, vol. 72(C), pages 106-118.
    8. De Vos, Jonas & Singleton, Patrick A., 2020. "Travel and cognitive dissonance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 525-536.
    9. Huang, Xiaoyan & (Jason) Cao, Xinyu & Yin, Jiangbin & Cao, Xiaoshu, 2019. "Can metro transit reduce driving? Evidence from Xi'an, China," Transport Policy, Elsevier, vol. 81(C), pages 350-359.
    10. De Vos, Jonas & Mouratidis, Kostas & Cheng, Long & Kamruzzaman, Md., 2021. "Does a residential relocation enable satisfying travel?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 188-201.
    11. Liu Yang & Yuanqing Wang & Yujun Lian & Zhongming Guo & Yuanyuan Liu & Zhouhao Wu & Tieyue Zhang, 2022. "Key Factors, Planning Strategy and Policy for Low-Carbon Transport Development in Developing Cities of China," IJERPH, MDPI, vol. 19(21), pages 1-14, October.

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