Artificial intelligence techniques prevalent in manufacturing supply chain for value creation

He Zhu; Imran Ali; Abdul Jabbar

doi:10.1504/IJBIS.2023.10057817

Artificial intelligence techniques prevalent in manufacturing supply chain for value creation

He Zhu, Imran Ali, Abdul Jabbar

Research output: Contribution to journal › Article › peer-review

Abstract

In recent years, supply chains (SC) have been in turmoil under the pandemic, posing significant challenges to manufacturing SC. As a result, more and more academics and practitioners are advocating using artificial intelligence (AI) technologies to improve SC performance. Evidence shows that AI technologies present opportunities for SC, but the application of AI in SC is currently in its infancy. Hence, a thorough review of the topic is necessary to understand the scholarly work in this area. The study uses a systematic literature review (SLR) to extract data from Scopus, EBSCO and ABI/INFORM databases from 2012-2023. 72 articles were reviewed. The descriptive and thematic analysis revealed various insights into themes and AI applications. The main challenges of AI identified in the study are organisational and social issues, regulations and accountability, data privacy and security and for value creation.

Original language	English
Journal	International Journal of Business Information Systems
DOIs	https://doi.org/10.1504/IJBIS.2023.10057817
Publication status	Accepted/In press - 15 Mar 2023

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Cite this

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title = "Artificial intelligence techniques prevalent in manufacturing supply chain for value creation",

abstract = "In recent years, supply chains (SC) have been in turmoil under the pandemic, posing significant challenges to manufacturing SC. As a result, more and more academics and practitioners are advocating using artificial intelligence (AI) technologies to improve SC performance. Evidence shows that AI technologies present opportunities for SC, but the application of AI in SC is currently in its infancy. Hence, a thorough review of the topic is necessary to understand the scholarly work in this area. The study uses a systematic literature review (SLR) to extract data from Scopus, EBSCO and ABI/INFORM databases from 2012-2023. 72 articles were reviewed. The descriptive and thematic analysis revealed various insights into themes and AI applications. The main challenges of AI identified in the study are organisational and social issues, regulations and accountability, data privacy and security and for value creation.",

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AU - Ali, Imran

AU - Jabbar, Abdul

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AB - In recent years, supply chains (SC) have been in turmoil under the pandemic, posing significant challenges to manufacturing SC. As a result, more and more academics and practitioners are advocating using artificial intelligence (AI) technologies to improve SC performance. Evidence shows that AI technologies present opportunities for SC, but the application of AI in SC is currently in its infancy. Hence, a thorough review of the topic is necessary to understand the scholarly work in this area. The study uses a systematic literature review (SLR) to extract data from Scopus, EBSCO and ABI/INFORM databases from 2012-2023. 72 articles were reviewed. The descriptive and thematic analysis revealed various insights into themes and AI applications. The main challenges of AI identified in the study are organisational and social issues, regulations and accountability, data privacy and security and for value creation.

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