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Application of machine learning in supply chain management: a comprehensive overview of the main areas
Citation
Tirkolaee, EB and Sadeghi, S and Mooseloo, FM and Vandchali, HR and Aeini, S, Application of machine learning in supply chain management: a comprehensive overview of the main areas, Mathematical Problems in Engineering, 2021 Article 1476043. ISSN 1024-123X (2021) [Refereed Article]
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Copyright Statement
Copyright © 2021 Erfan Babaee Tirkolaee et al. This is an open access article distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License, (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In today’s complex and ever-changing world, concerns about the lack of enough data have been replaced by concerns about too
much data for supply chain management (SCM). (e volume of data generated from all parts of the supply chain has changed the
nature of SCM analysis. By increasing the volume of data, the efficiency and effectiveness of the traditional methods have
decreased. Limitations of these methods in analyzing and interpreting a large amount of data have led scholars to generate some
methods that have high capability to analyze and interpret big data. (erefore, the main purpose of this paper is to identify the
applications of machine learning (ML) in SCM as one of the most well-known artificial intelligence (AI) techniques. By developing
a conceptual framework, this paper identifies the contributions of ML techniques in selecting and segmenting suppliers, predicting
supply chain risks, and estimating demand and sales, production, inventory management, transportation and distribution,
sustainable development (SD), and circular economy (CE). Finally, the implications of the study on the main limitations and
challenges are discussed, and then managerial insights and future research directions are given.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | machine learning, supply chain management |
| Research Division: | Commerce, Management, Tourism and Services |
| Research Group: | Transportation, logistics and supply chains |
| Research Field: | Supply chains |
| Objective Division: | Defence |
| Objective Group: | Defence |
| Objective Field: | Logistics |
| UTAS Author: | Vandchali, HR (Dr Hadi Rezaei Vandchali) |
| ID Code: | 145739 |
| Year Published: | 2021 |
| Web of Science® Times Cited: | 6 |
| Deposited By: | Maritime and Logistics Management |
| Deposited On: | 2021-08-04 |
| Last Modified: | 2021-09-24 |
| Downloads: | 6 View Download Statistics |
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