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Big Data Analytics in Supply Chain Management: A Systematic Literature Review and Research Directions
| Content Provider | MDPI |
|---|---|
| Author | Mangalaraj, George |
| Copyright Year | 2022 |
| Description | 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. |
| Starting Page | 17 |
| e-ISSN | 25042289 |
| DOI | 10.3390/bdcc6010017 |
| Journal | Big Data and Cognitive Computing |
| Issue Number | 1 |
| Volume Number | 6 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-02-01 |
| Access Restriction | Open |
| Subject Keyword | Big Data and Cognitive Computing Information and Library Science Big Data Analytics Data Analytics Supply Chain Management Sustainability Performances Scor Model Predictive Analytics |
| Content Type | Text |
| Resource Type | Article |
