Developing An Automated Approach Of Risk Analysis In Supply Chains Using AI

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.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.7148/2025-0412
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Developing An Automated Approach Of Risk Analysis In Supply Chains Using AI

Thorsten Claus, Frank Herrmann, Franz Vallée, Janis Purk
Supply Chain Resilience and Risk Management
article

Developing An Automated Approach Of Risk Analysis In Supply Chains Using AI

Thorsten Claus, Frank Herrmann, Franz Vallée, Janis Purk
article en

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.

Openalex Percentile: Top 73%
Supply Chain Resilience and Risk Management
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