Abstract
This paper reviews the role of machine learning in enhancing the resilience and sustainability of global value chains. Machine learning algorithms can provide insights into procurement relationships between companies, enhance supply chain visibility, and improve supply chain risk prediction. However, integrating machine learning into supply chain management faces challenges such as technology complexity, data privacy and security, and cultural barriers. Supply chain managers must have a proactive, innovative mindset and invest in necessary data infrastructure and organizational capabilities to exploit machine learning's potential. Future research could broaden the respondent base, consider other influencing factors like culture and management commitment, and examine disruptions' moderating effects and policy/governance aspects. Ultimately, integrating machine learning can enhance global value chain resilience and prepare for external shocks.