A comparative overview of aggregation methods of a graphical risk assessment: An analysis based on a critical infrastructure project
Albert Kutej,
Stefan Rass and
Rainer W Alexandrowicz
PLOS ONE, 2025, vol. 20, issue 6, 1-27
Abstract:
We compare the traditional risk and opportunity assessment method, which relies on fixed values for impacts (or potentials) and probabilities, with a graphical approach that incorporates the representation of uncertainties. To date, this graphical risk assessment method, in combination with subsequent opinion pooling, has neither been empirically studied nor validated. Therefore, its comparison with classical risk assessment remains an open question. Its significance lies in the need to validate the graphical method as a consistent generalization of the well-established classical risk assessment, which is based on expert-defined impact and probability specifications. To establish and test consistency between classical and graphical risk specifications, the latter requires appropriate aggregation methods to synthesize risk assessments from individual expert judgments—an independent challenge in itself. Therefore, various aggregation methods are introduced and tested using a case study in the field of critical infrastructure, based on expert interviews from multiple specialized domains. The collected data enables both qualitative and statistical analysis. The Kolmogorov-Smirnov and Wasserstein tests were employed to quantify differences between the methods, while overall significance was assessed using Fisher’s method. This study underscores the importance of integrating uncertainties into risk assessments and provides insights into the effectiveness and applicability of different aggregation methods.
Date: 2025
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0325267 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 25267&type=printable (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0325267
DOI: 10.1371/journal.pone.0325267
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().