IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i18p11634-d916805.html
   My bibliography  Save this article

Exploring Natural and Social Factors Affecting Road Disruption Patterns and the Duration of Recovery: A Case from Hiroshima, Japan

Author

Listed:
  • Rodelia Sansano

    (Graduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima 739-8529, Japan)

  • Makoto Chikaraishi

    (Graduate School for International Development and Cooperation, Hiroshima University, Hiroshima 739-8529, Japan)

Abstract

For the past few decades, the occurrence and severity of disasters have been increasing. This study empirically explores factors affecting road disruption patterns and the duration of road recovery based on the road network disruption and recovery record in Hiroshima, Japan, over the last 19 years, using (1) a binary logit model to identify factors affecting the disruption probability of each road link, and (2) a survival model to identify the factors affecting the recovery duration. We divided the factors into social and natural factors, where the former might be easier for policy makers to control. Results show that not only natural factors, but also social factors, particularly who manages the road, significantly affect both the probability of road disruptions and road recovery duration. This implies that the ability and available resources that each road manager has firstly affects the quality of the road, which in turn affects the probability of it being disrupted, and secondly affects the quickness of taking recovery actions. This points to potential avenues for improving coordination across cities, prefectures, and national road managers in managing roads during disasters.

Suggested Citation

  • Rodelia Sansano & Makoto Chikaraishi, 2022. "Exploring Natural and Social Factors Affecting Road Disruption Patterns and the Duration of Recovery: A Case from Hiroshima, Japan," Sustainability, MDPI, vol. 14(18), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11634-:d:916805
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/18/11634/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/18/11634/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, X. & Miller-Hooks, E. & Denny, K., 2015. "Assessing the role of network topology in transportation network resilience," Journal of Transport Geography, Elsevier, vol. 46(C), pages 35-45.
    2. Kermanshah, A. & Derrible, S., 2016. "A geographical and multi-criteria vulnerability assessment of transportation networks against extreme earthquakes," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 39-49.
    3. Nicholson, Alan & Du, Zhen-Ping, 1997. "Degradable transportation systems: An integrated equilibrium model," Transportation Research Part B: Methodological, Elsevier, vol. 31(3), pages 209-223, June.
    4. Ajam, Meraj & Akbari, Vahid & Salman, F. Sibel, 2019. "Minimizing latency in post-disaster road clearance operations," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1098-1112.
    5. Gokalp, Can & Patil, Priyadarshan N. & Boyles, Stephen D., 2021. "Post-disaster recovery sequencing strategy for road networks," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 228-245.
    6. Iloglu, Suzan & Albert, Laura A., 2020. "A maximal multiple coverage and network restoration problem for disaster recovery," Operations Research Perspectives, Elsevier, vol. 7(C).
    7. Gao, Lei & Liu, Xingquan & Liu, Yu & Wang, Pu & Deng, Min & Zhu, Qing & Li, Haifeng, 2019. "Measuring road network topology vulnerability by Ricci curvature," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    8. Sayarshad, Hamid R. & Du, Xinpi & Gao, H. Oliver, 2020. "Dynamic post-disaster debris clearance problem with re-positioning of clearance equipment items under partially observable information," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 352-372.
    9. 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).
    10. Johan Rose Santos & Nur Diana Safitri & Maya Safira & Varun Varghese & Makoto Chikaraishi, 2021. "Road network vulnerability and city-level characteristics: A nationwide comparative analysis of Japanese cities," Environment and Planning B, , vol. 48(5), pages 1091-1107, June.
    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. Boeing, Geoff & Ha, Jaehyun, 2024. "Resilient by design: Simulating street network disruptions across every urban area in the world," Transportation Research Part A: Policy and Practice, Elsevier, vol. 182(C).
    2. Akbari, Vahid & Shiri, Davood & Sibel Salman, F., 2021. "An online optimization approach to post-disaster road restoration," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 1-25.
    3. 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).
    4. Souza Almeida, Luana & Goerlandt, Floris & Pelot, Ronald, 2022. "Trends and gaps in the literature of road network repair and restoration in the context of disaster response operations," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    5. Rahimi-Golkhandan, Armin & Garvin, Michael J. & Brown, Bryan L., 2019. "Characterizing and measuring transportation infrastructure diversity through linkages with ecological stability theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 128(C), pages 114-130.
    6. Hong, Liu & Ye, Bowen & Yan, Han & Zhang, Hui & Ouyang, Min & (Sean) He, Xiaozheng, 2019. "Spatiotemporal vulnerability analysis of railway systems with heterogeneous train flows," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 725-744.
    7. Lu, Qing-Long & Sun, Wenzhe & Dai, Jiannan & Schmöcker, Jan-Dirk & Antoniou, Constantinos, 2024. "Traffic resilience quantification based on macroscopic fundamental diagrams and analysis using topological attributes," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    8. Hosseini, Yaser & Mohammadi, Reza Karami & Yang, Tony Y., 2024. "A comprehensive approach in post-earthquake blockage prediction of urban road network and emergency resilience optimization," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    9. Lu, Qing-Chang & Xu, Peng-Cheng & Zhang, Jingxiao, 2021. "Infrastructure-based transportation network vulnerability modeling and analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    10. Sedigheh Meimandi Parizi & Mohammad Taleai & Ayyoob Sharifi, 2021. "Integrated methods to determine urban physical resilience characteristics and their interactions," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(1), pages 725-754, October.
    11. Dong, Shangjia & Gao, Xinyu & Mostafavi, Ali & Gao, Jianxi & Gangwal, Utkarsh, 2023. "Characterizing resilience of flood-disrupted dynamic transportation network through the lens of link reliability and stability," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    12. Boeing, Geoff & Ha, Jaehyun, 2024. "Resilient by Design: Simulating Street Network Disruptions across Every Urban Area in the World," SocArXiv tk93y, Center for Open Science.
    13. He,Yiyi & Maruyama Rentschler,Jun Erik & Avner,Paolo & Gao,Jianxi & Yue,Xiangyu & Radke,John, 2022. "Mobility and Resilience : A Global Assessment of Flood Impacts on Road Transportation Networks," Policy Research Working Paper Series 10049, The World Bank.
    14. Gu, Yu & Fu, Xiao & Liu, Zhiyuan & Xu, Xiangdong & Chen, Anthony, 2020. "Performance of transportation network under perturbations: Reliability, vulnerability, and resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    15. Yao He & Yongchun Yang & Meimei Wang & Xudong Zhang, 2022. "Resilience Analysis of Container Port Shipping Network Structure: The Case of China," Sustainability, MDPI, vol. 14(15), pages 1-17, August.
    16. Lei Che & Jiangang Xu & Hong Chen & Dongqi Sun & Bao Wang & Yunuo Zheng & Xuedi Yang & Zhongren Peng, 2022. "Evaluation of the Spatial Effect of Network Resilience in the Yangtze River Delta: An Integrated Framework for Regional Collaboration and Governance under Disruption," Land, MDPI, vol. 11(8), pages 1-20, August.
    17. Yangyang Meng & Xiaofei Zhao & Jianzhong Liu & Qingjie Qi, 2023. "Dynamic Influence Analysis of the Important Station Evolution on the Resilience of Complex Metro Network," Sustainability, MDPI, vol. 15(12), pages 1-15, June.
    18. Kurmankhojayev, Daniyar & Li, Guoyuan & Chen, Anthony, 2024. "Link criticality index: Refinement, framework extension, and a case study," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    19. Zou, Qiling & Chen, Suren, 2019. "Enhancing resilience of interdependent traffic-electric power system," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    20. Mo, Baichuan & Koutsopoulos, Haris N. & Zhao, Jinhua, 2022. "Inferring passenger responses to urban rail disruptions using smart card data: A probabilistic framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).

    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:gam:jsusta:v:14:y:2022:i:18:p:11634-:d:916805. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.