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Changes in car and bus usage amid the COVID-19 pandemic: Relationship with land use and land price

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  • Kim, Suji
  • Lee, Sujin
  • Ko, Eunjeong
  • Jang, Kitae
  • Yeo, Jiho

Abstract

This study aimed to explore the impacts of COVID-19 on car and bus usage and their relationships with land use and land price. Large-scale trip data of car and bus usage in Daejeon, South Korea, were tested. We made a trip-chain-level data set to analyze travel behavior based on activity-based travel volumes. Hexagonal cells were used to capture geographical explanatory variables, and a mixed-effect regression model was adopted to determine the impacts of COVID-19. The modeling outcomes demonstrated behavioral differences associated with using cars and buses amid the pandemic. People responded to the pandemic by reducing their trips more intensively during the daytime and weekends. Moreover, they avoided crowded or shared spaces by reducing bus trips and trips toward commercial areas. In terms of social equity, trips of people living in wealthier areas decreased more than those of people living in lower-priced areas, especially trips by buses. The findings contribute to the previous literature by adding a fundamental reference for the different impacts of pandemics on two universal transportation modes.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:jotrge:v:96:y:2021:i:c:s0966692321002210
    DOI: 10.1016/j.jtrangeo.2021.103168
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    Cited by:

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    2. Purim Srisawat & Wuyi Zhang & Kassara Sukpatch & Wachira Wichitphongsa, 2023. "Tourist Behavior and Sustainable Tourism Policy Planning in the COVID-19 Era: Insights from Thailand," Sustainability, MDPI, vol. 15(7), pages 1-21, March.
    3. Elif Bozkaya & Levent Eriskin & Mumtaz Karatas, 2023. "Data analytics during pandemics: a transportation and location planning perspective," Annals of Operations Research, Springer, vol. 328(1), pages 193-244, September.
    4. Cho, Jung-Hoon & Kim, Dong-Kyu & Kim, Eui-Jin, 2022. "Multi-scale causality analysis between COVID-19 cases and mobility level using ensemble empirical mode decomposition and causal decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    5. Jiang, Shixiong & Cai, Canhuang, 2022. "Unraveling the dynamic impacts of COVID-19 on metro ridership: An empirical analysis of Beijing and Shanghai, China," Transport Policy, Elsevier, vol. 127(C), pages 158-170.
    6. Yaiza Montero-Lamas & Alfonso Orro & Margarita Novales & Francisco-Alberto Varela-García, 2022. "Analysis of the Relationship between the Characteristics of the Areas of Influence of Bus Stops and the Decrease in Ridership during COVID-19 Lockdowns," Sustainability, MDPI, vol. 14(7), pages 1-19, April.

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