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This paper conducts a systematic review of machine learning (ML) applications in logistics and supply chain management (LSCM), analyzing literature from 1994 to 2019. It identifies key trends, gaps in research, and suggests future directions for ML in LSCM, noting that most studies focus on transportation and manufacturing industries. The review highlights the limited adoption of ML in LSCM and emphasizes the need for increased understanding and integration of ML technologies in the field.

Author

williamvilela

Language

EN