Supply Chain Risk Management (SCRM) is an important aspect in maintaining supply chain stability and resilience amidst global uncertainty. This research aims to explore the role of big data analytics in identifying, assessing and managing hidden risks in the logistics and transportation sector. The method used is a systematic literature review with the PRISMA approach, which involves identification, screening, eligibility and inclusion of articles from international databases. The research results show that big data analytics can increase visibility, improve operational efficiency, and enable the detection of hidden risks that are beyond the reach of traditional methods. The implications of this research emphasize the importance of integrating big data analytics in SCRM practices to increase supply chain resilience and minimize the impact of disruptions.
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