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

Abstract

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 early-alert 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.