Criticality analysis of a country's transport network via an agent-based supply chain model

Assessing the performance of an economy in times of crisis is a difficult task. This study presents an agent-based model capturing the behaviour of firms facing transport and supply disruptions due to natural disasters, and shows possible paths to reinforce infrastructure and supply chain resilience. Building resilience against shocks has become a pillar of sustainability. By understanding how the different components of an economy interact in times of crisis, we can design resilience strategies that go beyond building walls or dams. We formulate an original agent-based model to explore a crucial pathway through which a disaster affects the economy: the transport-supply chain nexus. The model simulates the behaviour of firms facing transport and supply disruptions and estimates the resulting indirect losses. As an illustration, the model is used to assess the criticality of Tanzanian roads, which are vulnerable to floods. We report three main results. First, the model generates maps that identify the transport infrastructure assets that are most critical for specific supply chains: roads that are most important for food security are different from those supporting international trade, for instance. Second, economic losses from transport disruptions increase non-linearly with the duration of disruptions, highlighting the benefit from fast repairs. Third, by combining economic and transport modelling, we can consider a broader spectrum of interventions. Beyond strengthening the transport system, it is also possible to make supply chains more resilient to disruption with, for instance, sourcing decisions or inventory management.

Automated summary

This study presents an agent-based model that analyzes the behavior of firms facing transport and supply disruptions caused by natural disasters, and explores pathways to enhance infrastructure and supply chain resilience. The research findings show that different supply chains have varying levels of dependence on critical transport infrastructure assets, emphasizing the importance of rapid repairs for reducing economic losses from transport disruptions. By combining economic and transport modeling, a wider range of intervention measures can be considered to make supply chains more resilient to disruptions.