IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v95y2021ics0966692321002064.html
   My bibliography  Save this article

Exploring the dynamic impacts of COVID-19 on intercity travel in China

Author

Listed:
  • Li, Tao
  • Wang, Jiaoe
  • Huang, Jie
  • Yang, Wenyue
  • Chen, Zhuo

Abstract

Many studies have explored the effects of transportation and population movement on the spread of pandemics. However, little attention has been paid to the dynamic impact of pandemics on intercity travel and its recovery during a public health event period. Using intercity mobility and COVID-19 pandemic data, this study adopts the gradient boosting decision tree method to explore the dynamic effects of the COVID-19 on intercity travel in China. The influencing factors were classified into daily time-varying factors and time-invariant factors. The results show that China's intercity travel decreased on average by 51.35% from Jan 26 to Apr 7, 2020. Furtherly, the COVID-19 pandemic reduces intercity travel directly and indirectly by influencing industry development and transport connectivity. With the spread of COVID-19 and changes of control measures, the relationship between intercity travel and COVID-19, socio-economic development, transport is not linear. The relationship between intercity travel and secondary industry is illustrated by an inverted U-shaped curve from pre-pandemic to post-pandemic, whereas that with tertiary industry can be explained by a U-shaped curve. Meanwhile, this study highlights the dynamic effect of the COVID-19 on intercity mobility. These implications shed light on policies regarding the control measures during public health events that should include the dynamic impact of pandemics on intercity travel.

Suggested Citation

  • Li, Tao & Wang, Jiaoe & Huang, Jie & Yang, Wenyue & Chen, Zhuo, 2021. "Exploring the dynamic impacts of COVID-19 on intercity travel in China," Journal of Transport Geography, Elsevier, vol. 95(C).
    • Handle: RePEc:eee:jotrge:v:95:y:2021:i:c:s0966692321002064
    DOI: 10.1016/j.jtrangeo.2021.103153
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692321002064
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jtrangeo.2021.103153?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kuhnimhof, Tobias & Buehler, Ralph & Wirtz, Matthias & Kalinowska, Dominika, 2012. "Travel trends among young adults in Germany: increasing multimodality and declining car use for men," Journal of Transport Geography, Elsevier, vol. 24(C), pages 443-450.
    2. Beck, Matthew J. & Hensher, David A., 2020. "Insights into the impact of COVID-19 on household travel and activities in Australia – The early days of easing restrictions," Transport Policy, Elsevier, vol. 99(C), pages 95-119.
    3. Arbués, Pelayo & Baños, José F. & Mayor, Matías & Suárez, Patricia, 2016. "Determinants of ground transport modal choice in long-distance trips in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 131-143.
    4. Kim, Junghwan & Kwan, Mei-Po, 2021. "The impact of the COVID-19 pandemic on people's mobility: A longitudinal study of the U.S. from March to September of 2020," Journal of Transport Geography, Elsevier, vol. 93(C).
    5. Zhu, Zhenran & Zhang, Anming & Zhang, Yahua, 2018. "Connectivity of intercity passenger transportation in China: A multi-modal and network approach," Journal of Transport Geography, Elsevier, vol. 71(C), pages 263-276.
    6. Chen, Chia-Lin & Hall, Peter, 2012. "The wider spatial-economic impacts of high-speed trains: a comparative case study of Manchester and Lille sub-regions," Journal of Transport Geography, Elsevier, vol. 24(C), pages 89-110.
    7. Zhang, Yunchang & Fricker, Jon D., 2021. "Quantifying the impact of COVID-19 on non-motorized transportation: A Bayesian structural time series model," Transport Policy, Elsevier, vol. 103(C), pages 11-20.
    8. Beck, Matthew J. & Hensher, David A., 2020. "Insights into the impact of COVID-19 on household travel and activities in Australia – The early days under restrictions," Transport Policy, Elsevier, vol. 96(C), pages 76-93.
    9. Hamish Gibbs & Yang Liu & Carl A. B. Pearson & Christopher I. Jarvis & Chris Grundy & Billy J. Quilty & Charlie Diamond & Rosalind M. Eggo, 2020. "Changing travel patterns in China during the early stages of the COVID-19 pandemic," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    10. Jiwei Li & Qingqing Ye & Xuankai Deng & Yaolin Liu & Yanfang Liu, 2016. "Spatial-Temporal Analysis on Spring Festival Travel Rush in China Based on Multisource Big Data," Sustainability, MDPI, vol. 8(11), pages 1-16, November.
    11. (Ato) Xu, Wangtu & Zhou, Jiangping & Yang, Linchuan & Li, Ling, 2018. "The implications of high-speed rail for Chinese cities: Connectivity and accessibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 308-326.
    12. Michele Acuto & Shaun Larcom & Roger Keil & Mehrnaz Ghojeh & Tom Lindsay & Chiara Camponeschi & Susan Parnell, 2020. "Seeing COVID-19 through an urban lens," Nature Sustainability, Nature, vol. 3(12), pages 977-978, December.
    13. Eisenmann, Christine & Nobis, Claudia & Kolarova, Viktoriya & Lenz, Barbara & Winkler, Christian, 2021. "Transport mode use during the COVID-19 lockdown period in Germany: The car became more important, public transport lost ground," Transport Policy, Elsevier, vol. 103(C), pages 60-67.
    14. Xuemei Bai & Harini Nagendra & Peijun Shi & Haiyan Liu, 2020. "Cities: build networks and share plans to emerge stronger from COVID-19," Nature, Nature, vol. 584(7822), pages 517-520, August.
    15. Zhang, Yahua & Zhang, Anming & Wang, Jiaoe, 2020. "Exploring the roles of high-speed train, air and coach services in the spread of COVID-19 in China," Transport Policy, Elsevier, vol. 94(C), pages 34-42.
    16. Weiyang Zhang & Ben Derudder & Jianghao Wang & Frank Witlox, 2020. "An Analysis of the Determinants of the Multiplex Urban Networks in the Yangtze River Delta," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 111(2), pages 117-133, April.
    17. Haoran Yang & Frédéric Dobruszkes & Jiaoe Wang & Martin Dijst & Patrick Wiik, 2018. "Comparing China's urban systems in high-speed railway and airline networks," ULB Institutional Repository 2013/269363, ULB -- Universite Libre de Bruxelles.
    18. Dargay, Joyce M. & Clark, Stephen, 2012. "The determinants of long distance travel in Great Britain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 576-587.
    19. Ding, Chuan & Cao, Xinyu (Jason) & Næss, Petter, 2018. "Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 107-117.
    20. Wenjie Wu & Jianghao Wang & Tianshi Dai, 2016. "The Geography of Cultural Ties and Human Mobility: Big Data in Urban Contexts," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 106(3), pages 612-630, May.
    21. Garmendia, M. & Ureña, J.M. & Coronado, J.M., 2011. "Long-distance trips in a sparsely populated region: The impact of high-speed infrastructures," Journal of Transport Geography, Elsevier, vol. 19(4), pages 537-551.
    22. De Montis, Andrea & Chessa, Alessandro & Campagna, Michele & Caschili, Simone & Deplano, Giancarlo, 2010. "Modeling commuting systems through a complex network analysis: A study of the Italian islands of Sardinia and Sicily," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 2(3), pages 39-55.
    23. Wang, Jiaoe & Du, Delin & Huang, Jie, 2020. "Inter-city connections in China: High-speed train vs. inter-city coach," Journal of Transport Geography, Elsevier, vol. 82(C).
    24. Vickerman, Roger, 2021. "Will Covid-19 put the public back in public transport? A UK perspective," Transport Policy, Elsevier, vol. 103(C), pages 95-102.
    25. Wang, Jiaoe & Du, Delin & Ma, Li, 2021. "Geovisualizing cancelled air and high-speed train services during the outbreak of COVID-19 in China," Journal of Transport Geography, Elsevier, vol. 92(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Meng, Xin & Guo, Mingxue & Gao, Ziyou & Kang, Liujiang, 2023. "Interaction between travel restriction policies and the spread of COVID-19," Transport Policy, Elsevier, vol. 136(C), pages 209-227.
    3. Takahiro Yabe & Bernardo García Bulle Bueno & Xiaowen Dong & Alex Pentland & Esteban Moro, 2023. "Behavioral changes during the COVID-19 pandemic decreased income diversity of urban encounters," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    4. Zhou, Mingzhi & Zhou, Jiangping, 2024. "Multiscalar trip resilience and metro station-area characteristics: A case study of Hong Kong amid the pandemic," Journal of Transport Geography, Elsevier, vol. 116(C).
    5. Yan, Yingying & Zhong, Shiquan & Tian, Junfang & Jia, Ning, 2022. "An empirical study on consumer automobile purchase intentions influenced by the COVID-19 outbreak," Journal of Transport Geography, Elsevier, vol. 104(C).
    6. 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).
    7. Li, Tao & Cui, Leibo & Wang, Jiaoe, 2022. "New equilibrium? Dynamics of intercity mobility in China during COVID-19 pandemic period," Journal of Transport Geography, Elsevier, vol. 105(C).
    8. Ma, Qiwei & Liu, Anqi & Chen, Yuzhou & Tao, Ran, 2024. "Border effects for domestic travel in China during COVID-19 pandemic," Journal of Transport Geography, Elsevier, vol. 116(C).
    9. Yang, Binxin & Wu, Guangdong, 2023. "Multi-criteria analysis of cross-regional railways interconnection under the post COVID-19 pandemic crisis: A hybrid BWM-FAISM-DFS evaluation framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Chao & Feng, Tao & Gu, Xiaoning & Yao, Baozhen, 2022. "Investigating the effectiveness of COVID-19 pandemic countermeasures on the use of public transport: A case study of The Netherlands," Transport Policy, Elsevier, vol. 117(C), pages 98-107.
    2. Shuai Yu & Bin Li & Dongmei Liu, 2023. "Exploring the Public Health of Travel Behaviors in High-Speed Railway Environment during the COVID-19 Pandemic from the Perspective of Trip Chain: A Case Study of Beijing–Tianjin–Hebei Urban Agglomera," IJERPH, MDPI, vol. 20(2), pages 1-22, January.
    3. Huang, Yan & Zong, Huiming, 2020. "The spatial distribution and determinants of China’s high-speed train services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 56-70.
    4. Ali El Zein & Adrien Beziat & Pascal Pochet & Olivier Klein & Stephanie Vincent, 2022. "What drives the changes in public transport use in the context of the COVID‐19 pandemic? Highlights from Lyon metropolitan area," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S1), pages 122-141, November.
    5. Huang, Yan & Zong, Huiming, 2022. "The intercity railway connections in China: A comparative analysis of high-speed train and conventional train services," Transport Policy, Elsevier, vol. 120(C), pages 89-103.
    6. Soria, Jason & Edward, Deirdre & Stathopoulos, Amanda, 2023. "Requiem for transit ridership? An examination of who abandoned, who will return, and who will ride more with mobility as a service," Transport Policy, Elsevier, vol. 134(C), pages 139-154.
    7. Loa, Patrick & Hossain, Sanjana & Mashrur, Sk. Md. & Liu, Yicong & Wang, Kaili & Ong, Felita & Habib, Khandker Nurul, 2021. "Exploring the impacts of the COVID-19 pandemic on modality profiles for non-mandatory trips in the Greater Toronto Area," Transport Policy, Elsevier, vol. 110(C), pages 71-85.
    8. Shirgaokar, Manish & Reynard, Darcy & Collins, Damian, 2021. "Using twitter to investigate responses to street reallocation during COVID-19: Findings from the U.S. and Canada," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 300-312.
    9. Luan, Siliang & Yang, Qingfang & Jiang, Zhongtai & Wang, Wei, 2021. "Exploring the impact of COVID-19 on individual's travel mode choice in China," Transport Policy, Elsevier, vol. 106(C), pages 271-280.
    10. Mingke Xie & Yang Chen & Luliang Tang, 2022. "Exploring the Impact of Localized COVID-19 Events on Intercity Mobility during the Normalized Prevention and Control Period in China," IJERPH, MDPI, vol. 19(21), pages 1-16, November.
    11. Beck, Matthew J. & Hensher, David A. & Nelson, John D., 2021. "Public transport trends in Australia during the COVID-19 pandemic: An investigation of the influence of bio-security concerns on trip behaviour," Journal of Transport Geography, Elsevier, vol. 96(C).
    12. An, Yunlong & Lin, Xi & Li, Meng & He, Fang, 2021. "Dynamic governance decisions on multi-modal inter-city travel during a large-scale epidemic spreading," Transport Policy, Elsevier, vol. 104(C), pages 29-42.
    13. Chen, Yu & Lu, Yuqi & Jin, Cheng, 2024. "Spatiotemporal differentiation calendar for car and truck flow on expressways: A case study of Jiangsu, China," Journal of Transport Geography, Elsevier, vol. 116(C).
    14. Arbués, Pelayo & Baños, José F. & Mayor, Matías & Suárez, Patricia, 2016. "Determinants of ground transport modal choice in long-distance trips in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 131-143.
    15. Bagdatli, Muhammed Emin Cihangir & Ipek, Fatima, 2022. "Transport mode preferences of university students in post-COVID-19 pandemic," Transport Policy, Elsevier, vol. 118(C), pages 20-32.
    16. Liu, Shasha & Yamamoto, Toshiyuki, 2022. "Role of stay-at-home requests and travel restrictions in preventing the spread of COVID-19 in Japan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 1-16.
    17. Elizelle Juanee Cilliers & Shankar Sankaran & Gillian Armstrong & Sandeep Mathur & Mano Nugapitiya, 2021. "From Urban-Scape to Human-Scape: COVID-19 Trends That will Shape Future City Centres," Land, MDPI, vol. 10(10), pages 1-12, October.
    18. Wang, Chunan & Jiang, Changmin, 2022. "How do pandemics affect intercity air travel? Implications for traffic and environment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 330-353.
    19. Riccardo Ceccato & Riccardo Rossi & Massimiliano Gastaldi, 2021. "Travel Demand Prediction during COVID-19 Pandemic: Educational and Working Trips at the University of Padova," Sustainability, MDPI, vol. 13(12), pages 1-20, June.
    20. Möllers, Alessa & Specht, Sebastian & Wessel, Jan, 2022. "The impact of the Covid-19 pandemic and government intervention on active mobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 356-375.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jotrge:v:95:y:2021:i:c:s0966692321002064. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-transport-geography .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.