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dc.contributor.authorZhu, Hen_US
dc.contributor.authorAli, SIen_US
dc.contributor.authorJabbar, Aen_US
dc.date.accessioned2024-03-26T14:03:17Z
dc.date.available2023-03-15en_US
dc.identifier.issn1746-0980en_US
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/95768
dc.description.abstractIn 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 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. Seventy-two 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 & social issues, regulations & accountability, data privacy & security and for value creation.en_US
dc.publisherInderscienceen_US
dc.relation.ispartofInternational Journal of Business Information Systemsen_US
dc.subjectAIen_US
dc.subjectSupply Chainen_US
dc.subjectTechniquesen_US
dc.subjectManufacturingen_US
dc.subjectSystematic Literature Reviewen_US
dc.subjectSLRen_US
dc.titleArtificial Intelligence Techniques Prevalent in Manufacturing Supply Chain for Value Creationen_US
dc.typeArticle
pubs.notesNot knownen_US
pubs.publication-statusAccepteden_US
dcterms.dateAccepted2023-03-15en_US


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