A Systematic Investigation of the Integration of Machine Learning into Supply Chain Risk Management

The main objective of the paper is to analyze and synthesize existing scientific literature related supply chain areas where machine learning (ML) has already been implemented within risk management (SCRM) field, both in theory practice. Furthermore, we analyzed which risks were addressed use cases as well how ML might shape SCRM. For this purpose, conducted a systematic review. results showed that applied examples relate primarily early identification production, transport, order counteract potential problems quickly. Through case studies, able identify added value integration can bring SCRM (e.g., new data sources such social media or weather data). From analysis results, developed four propositions, be used motivation for further research.