The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.
Artificial intelligence in supply chain management: theory and applications
Abstract
Artificial intelligence (AI) was introduced to develop and create “thinking machines” that are capable of mimicking, learning, and replacing human intelligence. Since the late 1970s, AI has shown great promise in improving human decision-making processes and the subsequent productivity in various business endeavors due to its ability to recognise business patterns, learn business phenomena, seek information, and analyse data intelligently. Despite its widespread acceptance as a decision-aid tool, AI has seen limited application in supply chain management (SCM). To fully exploit the potential benefits of AI for SCM, this paper explores various sub-fields of AI that are most suitable for solving practical problems relevant to SCM. In so doing, this paper reviews the past record of success in AI applications to SCM and identifies the most fruitful areas of SCM in which to apply AI.
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Cites
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Cited by
Artificial Intelligence in Supply Chain Management: A Systematic Literature Review
Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., & Fischl, M. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2020.09.009 · Cited by 1,020
“A literature review by Min (2010) explores different subfields of AI that are suitable for solving practical problems relevant to SCM. Chong and Bai (2014) examine the predictors of open inter-organisational system adoption, using RosettaNet as a case study.”
BackgroundInfluentialCollins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2021.102383 · Cited by 783
Deep learning enabled inverse design in nanophotonics
So, S., Badloe, T., Noh, J., Rho, J., & Bravo‐Abad, J. (2020) · Nanophotonics · doi:10.1515/nanoph-2019-0474 · Cited by 564
Riahi, Y., Saikouk, T., Gunasekaran, A., & Badraoui, I. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2021.114702 · Cited by 400
Tsolakis, N., Schumacher, R., Dora, M., & Kumar, M. (2023) · Annals of Operations Research · doi:10.1007/s10479-022-04785-2 · Cited by 325
Metadata
- Authors
- Min, H.
- Venue
- International Journal of Logistics Research and Applications
- Publisher
- Informa UK Limited
- Published
- 2009-03-24
- Volume
- 13
- Issue
- 1
- Pages
- 13-39
- ISSN
- 1367-5567 (ISSN-L)
- 1469-848X
- OpenAlex
- W2117871237
- Cited by
- 573
- References
- 75
- FWCI
- 2.26
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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