Toorajipour, Reza, Sohrabpour, Vahid, Nazarpour, Ali, Oghazi, Pejvak and Fischi, Maria (2021) Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research, 122. pp. 502-517. ISSN 0148-2963
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Abstract
This paper seeks to identify the contributions of artificial intelligence (AI) to supply chain management (SCM)
through a systematic review of the existing literature. To address the current scientific gap of AI in SCM, this
study aimed to determine the current and potential AI techniques that can enhance both the study and practice of
SCM. Gaps in the literature that need to be addressed through scientific research were also identified. More
specifically, the following four aspects were covered: (1) the most prevalent AI techniques in SCM; (2) the potential AI techniques for employment in SCM; (3) the current AI-improved SCM subfields; and (4) the subfields
that have high potential to be enhanced by AI. A specific set of inclusion and exclusion criteria are used to
identify and examine papers from four SCM fields: logistics, marketing, supply chain and production. This paper
provides insights through systematic analysis and synthesis.
Item Type: | Article |
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Additional Information: | © 2020 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Cite as: Reza Toorajipour, Vahid Sohrabpour, Ali Nazarpour, Pejvak Oghazi, Maria Fischl, Artificial intelligence in supply chain management: A systematic literature review, Journal of Business Research, Volume 122, 2021, Pages 502-517, ISSN 0148-2963, https://doi.org/10.1016/j.jbusres.2020.09.009. |
Keywords: | Supply chain management; Systematic literature review; Artificial Intelligence; |
Academic Unit: | Faculty of Social Sciences > School of Business |
Item ID: | 14250 |
Identification Number: | 10.1016/j.jbusres.2020.09.009 |
Depositing User: | Ali Nazarpour |
Date Deposited: | 25 Mar 2021 15:23 |
Journal or Publication Title: | Journal of Business Research |
Publisher: | Elsevier |
Refereed: | Yes |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/14250 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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