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).

Supply chain resilience is more critical than ever amid unprecedented disruptions due to the COVID-19 pandemic. As a result, supply chains are viewed more as lifelines connecting business and society to goods and services -- from personal protective equipment to personal digital assistants -- with robotic process automation (RPA), artificial intelligence (AI) and machine learning pressed into service at an accelerated pace. Working virtually alongside humans or replacing them, RPA software bots are as essential as the front-line workers who keep the supply chain flowing from product conception to delivery. But the rush to take full advantage of RPA for highly repetitive, time-consuming tasks and AI for more complex supply chain processes is not without roadblocks as companies shift priorities, digitally transform and contend with the aftershocks of the pandemic. According to KPMG's 2020 Outlook, CEOs surveyed during July and August identified supply chain risk as one of the "greatest threats to their organizations' growth."