Methods for Assessing and Mitigating Risks in Logistics and Transportation

The research is devoted to the systematization and critical analysis of contemporary methods for assessing and reducing risks in the field of logistics and transportation. The purpose of the article is to describe an integrative risk-management methodology that combines traditional tools and innovative digital technologies. As its methodological basis, the study employs a systems analysis of scientific publications with an emphasis on predictive analytics, digital twins, and models of supply-chain resilience. The results of the investigation made it possible to classify key risks and their corresponding mitigation methods—from insurance mechanisms and inventory management to crisis response based on real-time operational data. The main achievement is the formation of a conceptual integrated model of logistics risk management that illustrates the synergistic interaction of proactive and reactive strategies. The scientific novelty of the work lies in proposing a comprehensive approach that unites predictive analytics and digital twins with traditional methods, which markedly enhances the adaptability and resilience of logistics systems under conditions of high uncertainty. A conclusion is formulated regarding the need to transition from static to dynamic, data-driven risk management to ensure long-term competitiveness. The materials obtained are of interest to academic researchers, managers of logistics companies, and supply-chain management professionals.