IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v628y2023ics037843712300729x.html
   My bibliography  Save this article

Identification of critical transportation cities in the multimodal transportation network of China

Author

Listed:
  • Shen, Jingwei
  • Zong, Huiming

Abstract

Critical transportation cities often have a disproportionate impact on the functioning of the transportation network, and identifying critical transportation cities may help improve the overall performance of the transportation network. In this study, critical transportation city identification in the multimodal transportation network of China is conducted. First, a directed weighted network that can express both the direction and strength of intercity links in China is constructed. Then, five indicators measuring node centrality are used to evaluate the importance of the nodes in the train network, bus network and flight network. Third, principal component analysis (PCA) is used to identify the critical transportation cities. Finally, the influencing factors of importance of transportation cities are quantitatively estimated by fitting the stepwise regression. The results show that (1) cities in North China, Central China, East China, and South China have higher comprehensive scores, while cities in Northeast China, Northwest China and Southwest China have lower scores; (2) provincial capital cities and some larger cities are generally the central transportation hubs of a region; and (3) the comprehensive score of Chinese cities is closely related to GDP, resident population, local general public budget expenditure, and loans of financial institutions at year end.

Suggested Citation

  • Shen, Jingwei & Zong, Huiming, 2023. "Identification of critical transportation cities in the multimodal transportation network of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
  • Handle: RePEc:eee:phsmap:v:628:y:2023:i:c:s037843712300729x
    DOI: 10.1016/j.physa.2023.129174
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037843712300729X
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2023.129174?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Shanmukhappa, Tanuja & Ho, Ivan Wang-Hei & Tse, Chi Kong, 2018. "Spatial analysis of bus transport networks using network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 295-314.
    2. Du, Zhouyang & Tang, Jinjun & Qi, Yong & Wang, Yiwei & Han, Chunyang & Yang, Yifan, 2020. "Identifying critical nodes in metro network considering topological potential: A case study in Shenzhen city—China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    3. Li, Jiawei & Wen, Xiangxi & Wu, Minggong & Liu, Fei & Li, Shuangfeng, 2020. "Identification of key nodes and vital edges in aviation network based on minimum connected dominating set," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    4. Du, Yuxian & Lin, Xi & Pan, Ye & Chen, Zhaoxin & Xia, Huan & Luo, Qian, 2023. "Identifying influential airports in airline network based on failure risk factors with TOPSIS," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    5. Zhang, Xu & Zhang, Wei & Lee, Paul Tae-Woo, 2020. "Importance rankings of nodes in the China Railway Express network under the Belt and Road Initiative," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 134-147.
    6. Höfer, Tim & Sunak, Yasin & Siddique, Hafiz & Madlener, Reinhard, 2016. "Wind farm siting using a spatial Analytic Hierarchy Process approach: A case study of the Städteregion Aachen," Applied Energy, Elsevier, vol. 163(C), pages 222-243.
    7. Zhou, Yaoming & Wang, Junwei & Huang, George Q., 2019. "Efficiency and robustness of weighted air transport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 14-26.
    8. Li, Zhitao & Tang, Jinjun & Zhao, Chuyun & Gao, Fan, 2023. "Improved centrality measure based on the adapted PageRank algorithm for urban transportation multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    9. Mao, Xia & Chen, Xiao, 2023. "Does airport construction narrow regional economic disparities in China?," Journal of Air Transport Management, Elsevier, vol. 108(C).
    10. Chakrabarti, Sandip & Kushari, Triparnee & Mazumder, Taraknath, 2022. "Does transportation network centrality determine housing price?," Journal of Transport Geography, Elsevier, vol. 103(C).
    11. Wandelt, Sebastian & Shi, Xing & Sun, Xiaoqian, 2021. "Estimation and improvement of transportation network robustness by exploiting communities," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    12. Hossain, Md. Murad & Alam, Sameer, 2017. "A complex network approach towards modeling and analysis of the Australian Airport Network," Journal of Air Transport Management, Elsevier, vol. 60(C), pages 1-9.
    13. Wang, Longjian & Zheng, Shaoya & Wang, Yonggang & Wang, Longfei, 2021. "Identification of critical nodes in multimodal transportation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    14. Kim, Seyun & Yoon, Yoonjin, 2019. "On node criticality of the Northeast Asian air route network," Journal of Air Transport Management, Elsevier, vol. 80(C), pages 1-1.
    15. Huang, Wencheng & Zhang, Yue & Yu, Yaocheng & Xu, Yifei & Xu, Minhao & Zhang, Rui & De Dieu, Gatesi Jean & Yin, Dezhi & Liu, Zhanru, 2021. "Historical data-driven risk assessment of railway dangerous goods transportation system: Comparisons between Entropy Weight Method and Scatter Degree Method," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    16. 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.
    17. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    18. Ma, Jun-Chao & Wang, Li & Jiang, Zhi-Qiang & Yan, Wanfeng & Zhou, Wei-Xing, 2021. "City logistics networks based on online freight orders in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    19. Wang, Jiaoe & Mo, Huihui & Wang, Fahui & Jin, Fengjun, 2011. "Exploring the network structure and nodal centrality of China’s air transport network: A complex network approach," Journal of Transport Geography, Elsevier, vol. 19(4), pages 712-721.
    20. Li, Chuchu & Lin, Qin & Huang, Dong & Grifoll, Manel & Yang, Dong & Feng, Hongxiang, 2023. "Is entropy an indicator of port traffic predictability? The evidence from Chinese ports," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).
    Full references (including those not matched with items on IDEAS)

    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. Li, Siping & Zhou, Yaoming & Kundu, Tanmoy & Sheu, Jiuh-Biing, 2021. "Spatiotemporal variation of the worldwide air transportation network induced by COVID-19 pandemic in 2020," Transport Policy, Elsevier, vol. 111(C), pages 168-184.
    2. Feng, Xiao & He, Shiwei & Li, Guangye & Chi, Jushang, 2021. "Transfer network of high-speed rail and aviation: Structure and critical components," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    3. Xiaoqian Sun & Sebastian Wandelt, 2021. "Robustness of Air Transportation as Complex Networks:Systematic Review of 15 Years of Research and Outlook into the Future," Sustainability, MDPI, vol. 13(11), pages 1-19, June.
    4. Zhang, Mengyao & Huang, Tao & Guo, Zhaoxia & He, Zhenggang, 2022. "Complex-network-based traffic network analysis and dynamics: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    5. Bingxue Qian & Ning Zhang, 2022. "Topology and Robustness of Weighted Air Transport Networks in Multi-Airport Region," Sustainability, MDPI, vol. 14(11), pages 1-15, June.
    6. Wei, Sheng & Zheng, Wei & Wang, Lei, 2021. "Understanding the configuration of bus networks in urban China from the perspective of network types and administrative division effect," Transport Policy, Elsevier, vol. 104(C), pages 1-17.
    7. Li, Tao & Rong, Lili, 2022. "Spatiotemporally complementary effect of high-speed rail network on robustness of aviation network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 95-114.
    8. Pan, Shouzheng & Yan, Hai & He, Jia & He, Zhengbing, 2021. "Vulnerability and resilience of transportation systems: A recent literature review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    9. Jia, Tao & Liu, Wenxuan & Liu, Xintao, 2021. "A cross-city exploratory analysis of the robustness of bus transit networks using open-source data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    10. Kim, Seyun & Yoon, Yoonjin, 2019. "On node criticality of the Northeast Asian air route network," Journal of Air Transport Management, Elsevier, vol. 80(C), pages 1-1.
    11. Zhou, Yaoming & Kundu, Tanmoy & Goh, Mark & Sheu, Jiuh-Biing, 2021. "Multimodal transportation network centrality analysis for Belt and Road Initiative," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    12. Nicanor García Álvarez & Belarmino Adenso-Díaz & Laura Calzada-Infante, 2021. "Maritime Traffic as a Complex Network: a Systematic Review," Networks and Spatial Economics, Springer, vol. 21(2), pages 387-417, June.
    13. Chung, Hye Min & Kwon, Oh Kyoung & Han, Ok Soon & Kim, Hwa-Joong, 2020. "Evolving network characteristics of the asian international aviation market: A weighted network approach," Transport Policy, Elsevier, vol. 99(C), pages 299-313.
    14. Wang, Ying & Zheng, Yunan & Shi, Xuelei & Liu, Yiguang, 2022. "An effective heuristic clustering algorithm for mining multiple critical nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).
    15. Wang, Ning & Gao, Ying & He, Jia-tao & Yang, Jun, 2022. "Robustness evaluation of the air cargo network considering node importance and attack cost," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    16. Wang, Junwei & Zhou, Yaoming & Huang, George Q., 2019. "Alternative pair in the airport network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 408-418.
    17. Deng, Yu & Zhang, Yahua & Wang, Kun, 2022. "An analysis of the Chinese scheduled freighter network during the first year of the COVID-19 pandemic," Journal of Transport Geography, Elsevier, vol. 99(C).
    18. Liu, Aijun & Li, Zengxian & Shang, Wen-Long & Ochieng, Washington, 2023. "Performance evaluation model of transportation infrastructure: Perspective of COVID-19," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    19. Zhang, Qiang & Pu, Shunhao & Luo, Lihua & Liu, Zhichao & Xu, Jie, 2022. "Revisiting important ports in container shipping networks: A structural hole-based approach," Transport Policy, Elsevier, vol. 126(C), pages 239-248.
    20. Li, Tao & Rong, Lili & Yan, Kesheng, 2019. "Vulnerability analysis and critical area identification of public transport system: A case of high-speed rail and air transport coupling system in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 55-70.

    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:phsmap:v:628:y:2023:i:c:s037843712300729x. 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: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.