Developing an automated approach of risk analysis in supply chains using AI
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
This paper aimed to identify existing approaches of automated risk management procedures for companies in their supply chains and to present an approach for automated risk analysis based on textual news using artificial intelligence. Methodologically, a structured literature review was carried out in the databases "Web of Science" and "Scopus", in which the relevant results were categorized by the aim of the presented approaches on the basis of the records' abstracts. Four approaches were categorized as “Textual risk evaluation using AI/LLM” and were presented in process flow diagrams. Including learnings from these approaches, a new framework for an automated risk analysis was developed. Further research efforts are recommended for optimization in the area of process models and prompt engineering for automated risk analysis.
Details
| Original language | English |
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| Title of host publication | Proceedings of the 39th ECMS International Conference on Modelling and Simulation, ECMS 2025 |
| Editors | Marco Scarpa, Salvatore Cavalieri, Salvatore Serrano, Fabrizio De Vita |
| Publisher | European Council for Modelling and Simulation |
| Pages | 412-418 |
| Number of pages | 7 |
| ISBN (electronic) | 978-3-937436-86-9, 978-3-937436-85-2 |
| Publication status | Published - 2025 |
| Peer-reviewed | Yes |
Publication series
| Series | Proceedings - European Council for Modelling and Simulation, ECMS |
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| Volume | 2025-June |
| ISSN | 2522-2414 |
Conference
| Title | 39th ECMS International Conference on Modelling and Simulation |
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| Abbreviated title | ECMS 2025 |
| Conference number | 39 |
| Duration | 24 - 27 June 2025 |
| Website | |
| Location | Università degli Studi di Catania |
| City | Catania |
| Country | Italy |
External IDs
| ORCID | /0000-0003-1862-181X/work/208075037 |
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Keywords
ASJC Scopus subject areas
Keywords
- artificial intelligence, automation, disruptions, early warning systems, large language models, risk management, Supply chain resilience, textual analysis