Abstract

Global disruptions—such as pandemics, geopolitical conflicts, climate crises, and cyber incidents—pose severe challenges to supply chain stability and business continuity. This review proposes a comprehensive model for risk management and supply chain resilience that integrates predictive analytics, digital twin technology, and adaptive governance frameworks. The model emphasizes the need for proactive risk identification, diversification of supply networks, and digital transformation to enhance transparency and responsiveness. Through an interdisciplinary approach combining systems theory, risk assessment methodologies, and network optimization, the paper explores how organizations can build agility and redundancy without compromising efficiency. It also examines case studies of global disruptions—including the COVID-19 pandemic and semiconductor shortages—to illustrate critical vulnerabilities and lessons learned. The study further highlights the role of data-driven decision-making, scenario modeling, and real-time monitoring tools in improving resilience across procurement, logistics, and distribution systems. Ultimately, the proposed model aims to guide policymakers, industry leaders, and researchers in developing strategic frameworks that ensure both operational stability and sustainability amid global uncertainty. The integration of technology, collaboration, and strategic foresight is presented as the cornerstone of resilient supply chains capable of adapting dynamically to future disruptions.