Reproducibility investigation of elicitation techniques in risk assessment for hydraulic turbines

Mounia Berdai, Antoine Tahan and Martin Gagnon

Journal of Risk Research, 2020, vol. 23, issue 3, 297-312

Abstract: Certain elicitation techniques exert some control on expert opinions by leading them to a consensus or to a specific choice. In the absence of such guidelines, experts rely on their own knowledge to formulate opinions. This can result in large dispersions and affects the decision maker’s judgment. In this situation, we wonder what the relevant elicitation techniques are and how we can help experts to express their knowledge. From literature review, it is hard to decide if elicitation techniques are equivalent or not, which justifies the reproducibility analysis that we carry out in this paper. In this study, multiple experts have been involved in order to predict the defect size in hydraulic turbines, according to four proposed elicitation techniques. The comparison between these techniques was performed based on a suggested algorithm using the area metric concept. Our Findings show that elicitation techniques with ‘support’ tend to limit variations between experts and might be suitable only when prior knowledge on the expected elicited variable is available. Otherwise, we can end up with a distorted opinion of the elicited variable and an erroneous risk assessment.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/13669877.2019.1569093 (text/html)
Access to full text is restricted to subscribers.

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:taf:jriskr:v:23:y:2020:i:3:p:297-312

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RJRR20

DOI: 10.1080/13669877.2019.1569093

Access Statistics for this article

Journal of Risk Research is currently edited by Bryan MacGregor

More articles in Journal of Risk Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().