Evidence and belief in regulatory decisions - Incorporating expected utility into decision modelling

  • Authors:

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

  • Affiliations:

  • University of Nottingham, School of Computer Science, Jubilee Campus, Wollaton Road, Nottingham NG8 1BB, UK;Cranfield University, Collaborative Centre of Excellence in Understanding and Managing Natural and Environmental Risks, School of Applied Sciences, Bedfordshire MK43 0AL, UK;University of Nottingham, School of Computer Science, Jubilee Campus, Wollaton Road, Nottingham NG8 1BB, UK;London School of Economics, Department of Management, London WC2A 2AE, UK;University of Nottingham Ningbo, Division of Computer Science, Ningbo 315100, China;Cranfield University, Collaborative Centre of Excellence in Understanding and Managing Natural and Environmental Risks, School of Applied Sciences, Bedfordshire MK43 0AL, UK;Cranfield University, Collaborative Centre of Excellence in Understanding and Managing Natural and Environmental Risks, School of Applied Sciences, Bedfordshire MK43 0AL, UK

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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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(TM)), 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.