Advancing the Sustainability of Risk Assessments within the Renewable Energy Sector—Review of Published Risk Assessments

Mark Jenkins, Sean Loughney, Dante Benjamin Matellini () and Jin Wang
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Mark Jenkins: James Parsons Building, School of Engineering, Liverpool John Moores University, 3 Byrom Street, Liverpool L3 3AF, UK
Sean Loughney: James Parsons Building, School of Engineering, Liverpool John Moores University, 3 Byrom Street, Liverpool L3 3AF, UK
Dante Benjamin Matellini: James Parsons Building, School of Engineering, Liverpool John Moores University, 3 Byrom Street, Liverpool L3 3AF, UK
Jin Wang: James Parsons Building, School of Engineering, Liverpool John Moores University, 3 Byrom Street, Liverpool L3 3AF, UK

Sustainability, 2024, vol. 16, issue 6, 1-15

Abstract: Repeated regulatory incident investigations demonstrate the insufficiency of company risk assessments and the vulnerabilities that this exposes to the business and its duty holders who are, ultimately, culpable for the subsequent legislative breaches. While the epistemology and taxonomy of the traditional risk assessment are well established, there is a paucity of information that allows the verification and validation of the risk assessment content. Using evidence-based methodologies such as Content Analysis, Thematic Analysis, and validating the outputs using a survey, it became possible to “reverse engineer” the risk assessment content. This analysis of the published risk assessments, kindly supplied by six different Renewable Energy businesses, established that deterministic and behavioristic risk management methodologies had been adopted. These methodologies permitted and guided the use of vague and imprecise terminology and phraseology, numerical inconsistencies resulting in data ossification, and flawed assumptions. This analysis enables the duty holders to make informed and rational judgements about the adequacy of the risk assessment documents, and the process that permitted and guided their creation.

Keywords: risk assessment; conformation bias; conflicting goals; renewable energy; compliance; determinism; linearity; causation; cognitive dissonance; total recordable injury rates (TRIR) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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