Recovery strategies for a disrupted supply chain network: Leveraging blockchain technology in pre- and post-disruption scenarios

Abstract

Supply chain networks have become larger, more complex and more challenging to manage, especially considering the multitude of risks and disruptions that may manifest. As such, a disruption can wreak havoc to a supply chain network, rendering the ability of a firm to respond to these disruptions with appropriate recovery strategies paramount. In this paper, we analyze such recovery strategies in a supply chain network. The specific model we develop aims at predicting a disruption that may occur in a context where smart contracts have been implemented based on blockchain technology. Within this setting, we suggest appropriate measures to be undertaken by an organization to mitigate the disruption and avoid negative performance outcomes as much as possible. If the disruption cannot be avoided, the proposed genetic algorithm-based approach focuses on adopting re-active measures to manage the post-disruption reality. As such, we effectively integrate both pre- and post-disruption scenarios to offer wholistic decision-support in an integrated fashion, extending prior work which mostly developed guidance only for either pre- or post-disruption responses. Specifically, we study the performance of a complex multi-echelon supply chain network, involving multiple suppliers, manufacturers, and distributors, under various conditions. The insights derived discern the effect of mitigation measures during a disruption, offering valuable guidance for decision makers.