Modeling the dynamic impacts of maritime network blockage on global supply chains  

作　　者：Shen Qu Yunlei She Qi Zhou Jasper Verschuur Lu-Tao Zhao Huan Liu Ming Xu Yi-Ming Wei 

机构地区：[1]Center for Energy and Environmental Policy Research,Beijing Institute of Technology,Beijing 100081,China [2]School of Management,Beijing Institute of Technology,Beijing 100081,China [3]Beijing Key Lab of Energy Economics and Environmental Management,Beijing 100081,China [4]Oxford Programme for Sustainable Infrastructure Systems(OPSIS),Environmental Change Institute,University of Oxford,OX12JD Oxford,UK [5]State Key Joint Laboratory of Environment Simulation and Pollution Control,School of Environment,Tsinghua University,Beijing 100084,China [6]State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex,Beijing 100084,China [7]School of Environment,Tsinghua University,Beijing 100084,China

出　　处：《The Innovation》2024年第4期103-109,102,共8页创新（英文）

基　　金：supported by the National Natural Science Foundation of China(72022004,52370189,and 52200228);National Key Research and Development Program Project(2021YFC3200205).

摘　　要：Recent phenomena such as pandemics,geopolitical tensions,and climate change-induced extreme weather events have caused transportation network interruptions,revealing vulnerabilities in the global supply chain.A salient example is the March 2021 Suez Canal blockage,which delayed 432 vessels carrying cargo valued at$92.7 billion,triggering widespread supply chain disruptions.Our ability to model the spatiotemporal ramifications of such incidents remains limited.To fill this gap,we develop an agent-based complex network model integrated with frequently updated maritime data.The Suez Canal blockage is taken as a case study.The results indicate that the effects of such blockages go beyond the directly affected countries and sectors.The Suez Canal blockage led to global losses of about$136.9($127.5–$147.3)billion,with India suffering 75%of these losses.Global losses show a nonlinear relationship with the duration of blockage and exhibit intricate trends post blockage.Our proposed model can be applied to diverse blockage scenarios,potentially acting as an earlyalert system for the ensuing supply chain impacts.Furthermore,high-resolution daily data post blockage offer valuable insights that can help nations and industries enhance their resilience against similar future events.

关 键 词：CHAINS VALUED EXTREME 

分 类 号：O17[理学—数学]