Leveraging Intelligent Recommender system as a first step resilience measure -- A data-driven supply chain disruption response framework

ABSTRACT In light of the Industry 4.0 era, the global pandemic, and wars, interest in deploying digital technologies to increase supply chain resilience (SCRes) is rising. The utilization of recommender systems as a supply chain (SC) resilience measure is neglected, although these systems can enhance SC resilience. To address this problem, this research proposed a data-driven supply chain disruption response framework based on intelligent recommender system techniques. A prototype implementation was conducted to validate the developed framework through a practical use case. Results show that the proposed framework can be implemented as an effective SC disruption mitigation measure in the SCRes response phase and help SC participants better react after the SC disruption. Keywords: Supply chain resilience, Disruption risk, Recommender System, Supply chain risk management, Decision Support System 1 INTRODUCTION Supply chains (SC) are becoming more sophisticated and complex with globalization, as well as more risks and uncertainty (Manners-Bell 2017).