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An exploration of the relationships between socioeconomics, land use and daily trip chain pattern among low-income residents

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  • Long Cheng
  • Xuewu Chen
  • Shuo Yang

Abstract

Daily trip chain complexity and type choices of low-income residents are examined based on activity travel diary survey data in Nanjing, China. Statistical tests reveal that non-work trip chain complexity is distinctly distinct between low-income residents and non-low-income residents. Low-income residents are inclined to make simple non-work chains. Two types of econometric models, a stereotype logit model and mixed logit model, are then developed to investigate the possible explanatory variables affecting their trip pattern. The number of stops within a chain and chain types are considered as dependent variables, while independent variables include household and personal characteristics as well as land use variables. Results show that once convenient and flexible conditions are supplied, low-income residents are more likely to make multiple activities in a trip chain. Areas with high population and employment densities are associated with complex work trip chains and more non-work activity involvement.

Suggested Citation

  • Long Cheng & Xuewu Chen & Shuo Yang, 2016. "An exploration of the relationships between socioeconomics, land use and daily trip chain pattern among low-income residents," Transportation Planning and Technology, Taylor & Francis Journals, vol. 39(4), pages 358-369, June.
    • Handle: RePEc:taf:transp:v:39:y:2016:i:4:p:358-369
    DOI: 10.1080/03081060.2016.1160579
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    Cited by:

    1. Kim, Suji & Lee, Sujin & Ko, Eunjeong & Jang, Kitae & Yeo, Jiho, 2021. "Changes in car and bus usage amid the COVID-19 pandemic: Relationship with land use and land price," Journal of Transport Geography, Elsevier, vol. 96(C).
    2. Yadi Zhu & Feng Chen & Ming Li & Zijia Wang, 2018. "Inferring the Economic Attributes of Urban Rail Transit Passengers Based on Individual Mobility Using Multisource Data," Sustainability, MDPI, vol. 10(11), pages 1-17, November.
    3. Wan, Li & Tang, Junqing & Wang, Lihua & Schooling, Jennifer, 2021. "Understanding non-commuting travel demand of car commuters – Insights from ANPR trip chain data in Cambridge," Transport Policy, Elsevier, vol. 106(C), pages 76-87.
    4. Yang, Shuo & Fan, Yingling & Deng, Wei & Cheng, Long, 2019. "Do built environment effects on travel behavior differ between household members? A case study of Nanjing, China," Transport Policy, Elsevier, vol. 81(C), pages 360-370.
    5. Gang Cheng & Shuzhi Zhao & Jin Li, 2019. "The Effects of Latent Attitudinal Variables and Sociodemographic Differences on Travel Behavior in Two Small, Underdeveloped Cities in China," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    6. Huang, Yuqiao & Gao, Linjie & Ni, Anning & Liu, Xiaoning, 2021. "Analysis of travel mode choice and trip chain pattern relationships based on multi-day GPS data: A case study in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 93(C).
    7. Cong Qi & Zhenjun Zhu & Xiucheng Guo & Ruiying Lu & Junlan Chen, 2020. "Examining Interrelationships between Tourist Travel Mode and Trip Chain Choices Using the Nested Logit Model," Sustainability, MDPI, vol. 12(18), pages 1-15, September.

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