Evidence map›Paper›PMID 40471934›Full record

ArticlePloS one2025

A comparative overview of aggregation methods of a graphical risk assessment: An analysis based on a critical infrastructure project.

Albert Kutej, Stefan Rass, Rainer W Alexandrowicz

Abstract readComparative Study
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Albert KutejUniversity of Klagenfurt, Klagenfurt, Austria.ORCID https://orcid.org/0009-0001-5952-3338
Stefan RassSecure Systems Group, LIT Secure and Correct Systems Lab, Johannes Kepler University, Linz, Austria.ORCID https://orcid.org/0000-0003-2821-2489
Rainer W AlexandrowiczDepartment of Methodology, Institute of Psychology, University of Klagenfurt, Klagenfurt, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID40471934
PMCPMC12140274

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.