Interpretive structural modeling of supply chain leagility during COVID-19

Abstract In the context of COVID-19 crisis, the Moroccan automotive ecosystem is uncertain and volatile. To survive in this changed environment, automotive organizations should manage effectively their leagile supply chains. This management depends mainly on the identification of the leagile enablers influencing the supply chain. To understand the relationship between these enablers, we used interpretive structural modeling (ISM) approach followed by MICMAC analysis. The presentation of a case study from the Moroccan automotive industry illustrates this approach. As a result, we classified enablers according to their driving and dependence power. This classification helps supply chain managers to improve supply chain leagility and performance in order to meet quickly the changed customer needs.