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Exploring the Topological Characteristics of Complex Public Transportation Networks: Focus on Variations in Both Single and Integrated Systems in the Seoul Metropolitan Area

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  • Jungyeol Hong

    (Department of Transportation Engineering, University of Seoul, Seoul 02504, Korea)

  • Reuben Tamakloe

    (Department of Transportation Engineering, University of Seoul, Seoul 02504, Korea)

  • Soobeom Lee

    (Department of Transportation Engineering, University of Seoul, Seoul 02504, Korea)

  • Dongjoo Park

    (Department of Transportation Engineering, University of Seoul, Seoul 02504, Korea)

Abstract

Many cities have integrated their public transportation modes to provide increased accessibility and reduced commute times. However, current transport network topology studies have focused on unimodal networks. Therefore, it is of significant interest for policymakers to examine the topology of integrated public transportation networks and to assess strategies for improving them. The objective of this study was to discuss a comprehensive analysis of an integrated public transportation network using graph theory, compare its characteristics to unimodal networks, and draw insights for improving their performance. Results demonstrate pertinent information concerning the structural composition of the Seoul Metropolitan Area’s (SMA) public transportation network. Despite the integration, the spatial configuration of the network was found to have low fault tolerance. However, the highly agglomerated community structure validated the robustness of integrated networks. Network centrality measures confirmed that integration improves connectivity and spatial accessibility to suburbs within the city. The study found that the SMA’s current public transportation network possesses structural defects that need to be addressed to improve its resilience and performance. Based on the outcomes of this study, the strategic creation or relocation of stations, and the construction of more links, is imperative for the enhancement of mobility.

Suggested Citation

  • Jungyeol Hong & Reuben Tamakloe & Soobeom Lee & Dongjoo Park, 2019. "Exploring the Topological Characteristics of Complex Public Transportation Networks: Focus on Variations in Both Single and Integrated Systems in the Seoul Metropolitan Area," Sustainability, MDPI, vol. 11(19), pages 1-26, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5404-:d:272119
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    References listed on IDEAS

    as
    1. Qing-Chang Lu & Shan Lin, 2019. "Vulnerability Analysis of Urban Rail Transit Network within Multi-Modal Public Transport Networks," Sustainability, MDPI, vol. 11(7), pages 1-14, April.
    2. Bae, Joonhyun & Kim, Sangwook, 2014. "Identifying and ranking influential spreaders in complex networks by neighborhood coreness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 549-559.
    3. Jiangang Shi & Shiping Wen & Xianbo Zhao & Guangdong Wu, 2019. "Sustainable Development of Urban Rail Transit Networks: A Vulnerability Perspective," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    4. Aziz, A. & Nawaz, M.S. & Nadeem, M. & Afzal, L., 2018. "Examining suitability of the integrated public transport system: A case study of Lahore," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 13-25.
    5. Soh, Harold & Lim, Sonja & Zhang, Tianyou & Fu, Xiuju & Lee, Gary Kee Khoon & Hung, Terence Gih Guang & Di, Pan & Prakasam, Silvester & Wong, Limsoon, 2010. "Weighted complex network analysis of travel routes on the Singapore public transportation system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5852-5863.
    6. Jiang, Ruoyun & Lu, Qing-Chang & Peng, Zhong-Ren, 2018. "A station-based rail transit network vulnerability measure considering land use dependency," Journal of Transport Geography, Elsevier, vol. 66(C), pages 10-18.
    7. Zhang, Lin & Lu, Jian & Fu, Bai-bai & Li, Shu-bin, 2019. "Dynamics analysis for the hour-scale based time-varying characteristic of topology complexity in a weighted urban rail transit network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    8. Liu, Jian-Guo & Ren, Zhuo-Ming & Guo, Qiang, 2013. "Ranking the spreading influence in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4154-4159.
    9. Andrea Landherr & Bettina Friedl & Julia Heidemann, 2010. "A Critical Review of Centrality Measures in Social Networks," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 2(6), pages 371-385, December.
    10. Wei Yu & Jun Chen & Xingchen Yan, 2019. "Space‒Time Evolution Analysis of the Nanjing Metro Network Based on a Complex Network," Sustainability, MDPI, vol. 11(2), pages 1-17, January.
    11. Yasir Tariq Mohmand & Aihu Wang, 2014. "Complex Network Analysis of Pakistan Railways," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-5, March.
    12. Seongman Jang & Youngsoo An & Changhyo Yi & Seungil Lee, 2017. "Assessing the spatial equity of Seoul’s public transportation using the Gini coefficient based on its accessibility," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 21(1), pages 91-107, January.
    13. Jingyi Lin & Yifang Ban, 2013. "Complex Network Topology of Transportation Systems," Transport Reviews, Taylor & Francis Journals, vol. 33(6), pages 658-685, November.
    14. Zhuangbin Shi & Ning Zhang & Yang Liu & Wei Xu, 2018. "Exploring Spatiotemporal Variation in Hourly Metro Ridership at Station Level: The Influence of Built Environment and Topological Structure," Sustainability, MDPI, vol. 10(12), pages 1-16, December.
    15. Liu, Jun & Xiong, Qingyu & Shi, Weiren & Shi, Xin & Wang, Kai, 2016. "Evaluating the importance of nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 209-219.
    16. Chen, Duanbing & Lü, Linyuan & Shang, Ming-Sheng & Zhang, Yi-Cheng & Zhou, Tao, 2012. "Identifying influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1777-1787.
    17. Du, Yuxian & Gao, Cai & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2014. "A new method of identifying influential nodes in complex networks based on TOPSIS," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 57-69.
    18. Cervero, Robert & Kang, Chang Deok, 2011. "Bus rapid transit impacts on land uses and land values in Seoul, Korea," Transport Policy, Elsevier, vol. 18(1), pages 102-116, January.
    19. Rui Ding & Norsidah Ujang & Hussain bin Hamid & Jianjun Wu, 2015. "Complex Network Theory Applied to the Growth of Kuala Lumpur’s Public Urban Rail Transit Network," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-22, October.
    20. 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.
    21. Mishra, Sabyasachee & Welch, Timothy F. & Jha, Manoj K., 2012. "Performance indicators for public transit connectivity in multi-modal transportation networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(7), pages 1066-1085.
    22. Yang, Yu & He, Ze & Song, Zouying & Fu, Xin & Wang, Jianwei, 2018. "Investigation on structural and spatial characteristics of taxi trip trajectory network in Xi’an, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 755-766.
    23. Sybil Derrible, 2012. "Network Centrality of Metro Systems," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-10, July.
    24. John C. Sutton, 2005. "GIS Applications in Transit Planning and Operations: A Review of Current Practice, Effective Applications and Challenges in the USA," Transportation Planning and Technology, Taylor & Francis Journals, vol. 28(4), pages 237-250, July.
    25. Anthony Chen & Chao Yang & Sirisak Kongsomsaksakul & Ming Lee, 2007. "Network-based Accessibility Measures for Vulnerability Analysis of Degradable Transportation Networks," Networks and Spatial Economics, Springer, vol. 7(3), pages 241-256, September.
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    Cited by:

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    2. Kopsidas, Athanasios & Kepaptsoglou, Konstantinos, 2022. "Identification of critical stations in a Metro System: A substitute complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    3. Yajun Xiong & Hui Tang & Xiaobo Tian, 2022. "Research on Structural Toughness of Railway City Network in Yellow River Basin and Case Study of Zhengzhou 7–20 Rainstorm Disaster," Sustainability, MDPI, vol. 14(19), pages 1-17, September.
    4. Carlos Rosa-Jiménez & Sergio Gutiérrez-Coronil & María José Márquez-Ballesteros & Alberto E. García-Moreno, 2023. "Relating Spatial Quality of Public Transportation and the Most Visited Museums: Revisiting Sustainable Mobility of Waterfronts and Historic Centers in International Cruise Destinations," Sustainability, MDPI, vol. 15(3), pages 1-23, January.
    5. Yangyang Meng & Qingjie Qi & Jianzhong Liu & Wei Zhou, 2022. "Dynamic Evolution Analysis of Complex Topology and Node Importance in Shenzhen Metro Network from 2004 to 2021," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    6. Kim, Minjun & Cho, Gi-Hyoug, 2021. "Analysis on bike-share ridership for origin-destination pairs: Effects of public transit route characteristics and land-use patterns," Journal of Transport Geography, Elsevier, vol. 93(C).
    7. Qingjie Qi & Yangyang Meng & Xiaofei Zhao & Jianzhong Liu, 2022. "Resilience Assessment of an Urban Metro Complex Network: A Case Study of the Zhengzhou Metro," Sustainability, MDPI, vol. 14(18), pages 1-19, September.
    8. Yuchen Qin & Yikang Zhang & Minfeng Yao & Qiwei Chen, 2023. "How to Measure the Impact of Walking Accessibility of Suburban Rail Station Catchment Areas on the Commercial Premium Benefits of Joint Development," Sustainability, MDPI, vol. 15(6), pages 1-29, March.

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