Supply chain risk management and artificial intelligence: state of the art and future research directions

Supply chain risk management (SCRM) encompasses a wide variety of strategies aiming to identify, assess, mitigate and monitor unexpected events or conditions which might have an impact, mostly adverse, on any part of a supply chain. SCRM strategies often depend on rapid and adaptive decision-making...

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Bibliographic Details
Published in:International journal of production research 2019-04, Vol.57 (7), p.2179-2202
Main Authors: Baryannis, George, Validi, Sahar, Dani, Samir, Antoniou, Grigoris
Format: Article
Language:English
Subjects:
Analytics
Artificial intelligence
Data management
Decision making
Literature reviews
Machine learning
Mapping
Mathematical programming
Multidimensional data
Risk
Risk management
SCRM strategy
supply chain disruption
Supply chain management
supply chain risk management
Supply chains
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Summary:Supply chain risk management (SCRM) encompasses a wide variety of strategies aiming to identify, assess, mitigate and monitor unexpected events or conditions which might have an impact, mostly adverse, on any part of a supply chain. SCRM strategies often depend on rapid and adaptive decision-making based on potentially large, multidimensional data sources. These characteristics make SCRM a suitable application area for artificial intelligence (AI) techniques. The aim of this paper is to provide a comprehensive review of supply chain literature that addresses problems relevant to SCRM using approaches that fall within the AI spectrum. To that end, an investigation is conducted on the various definitions and classifications of supply chain risk and related notions such as uncertainty. Then, a mapping study is performed to categorise existing literature according to the AI methodology used, ranging from mathematical programming to Machine Learning and Big Data Analytics, and the specific SCRM task they address (identification, assessment or response). Finally, a comprehensive analysis of each category is provided to identify missing aspects and unexplored areas and propose directions for future research at the confluence of SCRM and AI.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2018.1530476