This study aims to examine the robustness and resilience of supply chain networks under various disruption scenarios, focusing on how these disruptions propagate through the network, a phenomenon known as the ripple effect.
A theoretical model is developed to assess product flow through a multi-echelon supply chain under demand uncertainties. Within this setting, numerical analysis is conducted to measure the customer fill rate and at the same time to assess the impact of disruptions at the final echelon, capturing the ripple effect from distant nodes.
The study provides insights into the types and intensities of risks faced by multi-echelon supply chain networks. It highlights the repercussions of disruptions and identifies recovery measures to minimize and manage their impact, enabling the system to regain stability.
This research contributes to a deeper understanding of supply chain risks and their management by exploring the ripple effect in multi-echelon supply chains and offering strategies to enhance network resilience and robustness.
