145739-Application of machine learning in supply chain management.pdf (1.33 MB)
Application of machine learning in supply chain management: a comprehensive overview of the main areas
journal contribution
posted on 2023-05-21, 01:21 authored by Tirkolaee, EB, Sadeghi, S, Mooseloo, FM, Hadi Rezaei VandchaliHadi Rezaei Vandchali, Aeini, SIn today’s complex and ever-changing world, concerns about the lack of enough data have been replaced by concerns about too much data for supply chain management (SCM).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.
History
Publication title
Mathematical Problems in EngineeringVolume
2021Article number
1476043Number
1476043Pagination
1-14ISSN
1024-123XDepartment/School
Australian Maritime CollegePublisher
Hindawi LimitedPlace of publication
United KingdomRights 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.Repository Status
- Open