Abstract
Worries about insufficient data have given way to worries about an excess of data in the realm of supply chain management (SCM) in today's intricate and constantly evolving world. The substantial increase in data generated throughout the apparel supply chain has transformed the landscape of SCM analysis. The effectiveness and efficiency of earlier processes have dwindled with the surge in data volume. Due to the constraints of current methodologies in handling and deciphering extensive datasets, researchers have devised novel approaches capable of analyzing and interpreting vast amounts of data. Consequently, the main objective of this study is to explore the applications of machine learning (ML) within the Apparel Supply Chain, recognized as one of the prominent artificial intelligences (AI) methodologies.
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