Paper Title
SYSTEMATIC LITERATURE REVIEW OF MACHINE LEARNING IN SUPPLY CHAIN MANAGEMENT

Abstract
Abstract - The primary objective of this article is to conduct a comprehensive evaluation and synthesis of the latest literature on integrating Machine Learning within the topic of Supply Chain Management. In addition, a review has been done to determine which fields/ disciplines were included in the reviewed literature and how Machine Learning may impact Supply Chain Management. Therefore, a Systematic Literature Review was conducted through a search of titles using the keywords “Machine Learning” and “Supply Chain Management” in peer-reviewed articles throughout databases like “Google Scholar,” “Springer,” and “Elsevier” during the time frame from 2018 to 2022. This article provides answers to the inquiries and concerns explored in the Methodology Section using a comprehensive analysis of the chosen articles. In conclusion, the results of the Systematic Literature Review led to the initiation of discussions that may catalyze future research articles. Keywords - Supply Chain Management, Machine Learning, Systematic Literature Review, Digitalization, Supply Chain 4.0, Supply Chain Analytics.