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Cited by 409

The DOI matches its Crossref record; 92 of the 92 references it cites were found in a registry or an index.

Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review

Open access
Zamani, Efpraxia D., Smyth, Conn, Gupta, Samrat, Dennehy, Denis·2023·Annals of Operations Research
DOI 10.1007/s10479-022-04983-y
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Abstract

Artificial Intelligence (AI) and Big Data Analytics (BDA) have the potential to significantly improve resilience of supply chains and to facilitate more effective management of supply chain resources. Despite such potential benefits and the increase in popularity of AI and BDA in the context of supply chains, research to date is dispersed into research streams that is largely based on the publication outlet. We curate and synthesise this dispersed knowledge by conducting a systematic literature review of AI and BDA research in supply chain resilience that have been published in the Chartered Association of Business School (CABS) ranked journals between 2011 and 2021. The search strategy resulted in 522 studies, of which 23 were identified as primary papers relevant to this research. The findings advance knowledge by (i) assessing the current state of AI and BDA in supply chain literature, (ii) identifying the phases of supply chain resilience (readiness, response, recovery, adaptability) that AI and BDA have been reported to improve, and (iii) synthesising the reported benefits of AI and BDA in the context of supply chain resilience.

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Metadata

Authors
Zamani, E. D., Smyth, C., Gupta, S., & Dennehy, D.
Venue
Annals of Operations Research
Publisher
Springer Science and Business Media LLC
Published
2022-09-30
Volume
327
Issue
2
Pages
605-632
ISSN
  • 0254-5330 (ISSN-L)
  • 1572-9338
DOI
10.1007/s10479-022-04983-y
OpenAlex
W4298132459
Cited by
409
References
92
FWCI
12.97
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review. https://app.cochat.ai/papers/10.1007/s10479-022-04983-y
The paper
Zamani, E. D., Smyth, C., Gupta, S., & Dennehy, D. (2023). Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review. Annals of Operations Research. https://doi.org/10.1007/s10479-022-04983-y

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.