Evidence and belief in regulatory decisions – incorporating expected utility into decision modelling

Li, Jiawei; Davies, G.J.; Kendall, G.; Soane, E.; Bai, R.; Rocks, S.A.; Pollard, S.J.T.

Abstract

Recent changes in the assessment and management of risks has had the effect that greater importance has been placed on relationships between individuals and within groups to inform decision making. In this paper, we provide the theoretical underpinning for an expected utility approach to decision-making. The approach, which is presented using established evidence support logic (TESLA™), integrating the expected utilities in the forming of group decisions. The rationale and basis are described and illustrated through a hypothetical decision context of options for the disposal of animal carcasses that accumulate during disease outbreaks. The approach forms the basis for exploring the richness of risk-based decisions, and representing individual beliefs about the sufficiency of evidence they may advance in support of hypotheses.

Citation

Li, J., Davies, G., Kendall, G., Soane, E., Bai, R., Rocks, S., & Pollard, S. (2012). Evidence and belief in regulatory decisions – incorporating expected utility into decision modelling. Expert Systems with Applications, 39(10), https://doi.org/10.1016/j.eswa.2012.01.193

• Journal Article Type: Article
• Acceptance Date: Jan 4, 2012
• Online Publication Date: Feb 11, 2012
• Publication Date: Aug 1, 2012
• Deposit Date: Jun 29, 2018
• Publicly Available Date: Jun 29, 2018
• Journal: Expert Systems with Applications
• Print ISSN: 0957-4174
• Electronic ISSN: 0957-4174
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 39
• Issue: 10
• DOI: https://doi.org/10.1016/j.eswa.2012.01.193
• Keywords: Decision support; Uncertainty; Risk; Group decision making; Evidence support logic; Expected utility; TESLA™
• Public URL: https://nottingham-repository.worktribe.com/output/1006890
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0957417412002217?via%3Dihub