Big Data Analytics in Supply Chain Management: A Systematic Literature Review and Research Directions

Big data analytics has been successfully used for various business functions, such as accounting, marketing, supply chain, and operations. Currently, along with the recent development in machine learning and computing infrastructure, big data analytics in the supply chain are surging in importance....

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Bibliographic Details
Published in:Big data and cognitive computing 2022-03, Vol.6 (1), p.17
Main Authors: Lee, In, Mangalaraj, George
Format: Article
Language:English
Subjects:
Algorithms
Bibliometrics
Big Data
big data analytics
Cost control
Data analysis
data analytics
Data mining
Decision making
Digital libraries
Interdisciplinary aspects
Literature reviews
Machine learning
Mathematical analysis
Operations management
Predictive analytics
SCOR model
Supply chain management
Supply chains
sustainability
Systematic review
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Summary:Big data analytics has been successfully used for various business functions, such as accounting, marketing, supply chain, and operations. Currently, along with the recent development in machine learning and computing infrastructure, big data analytics in the supply chain are surging in importance. In light of the great interest and evolving nature of big data analytics in supply chains, this study conducts a systematic review of existing studies in big data analytics. This study presents a framework of a systematic literature review from interdisciplinary perspectives. From the organizational perspective, this study examines the theoretical foundations and research models that explain the sustainability and performances achieved through the use of big data analytics. Then, from the technical perspective, this study analyzes types of big data analytics, techniques, algorithms, and features developed for enhanced supply chain functions. Finally, this study identifies the research gap and suggests future research directions.
ISSN:2504-2289
2504-2289
DOI:10.3390/bdcc6010017