Literature DB >> 23834916

Eliciting and Combining Decision Criteria Using a Limited Palette of Utility Functions and Uncertainty Distributions: Illustrated by Application to Pest Risk Analysis.

Johnson Holt1,2, Adrian W Leach2, Gritta Schrader3, Françoise Petter4, Alan MacLeod5, Dirk Jan van der Gaag6, Richard H A Baker5, John D Mumford2.   

Abstract

Utility functions in the form of tables or matrices have often been used to combine discretely rated decision-making criteria. Matrix elements are usually specified individually, so no one rule or principle can be easily stated for the utility function as a whole. A series of five matrices are presented that aggregate criteria two at a time using simple rules that express a varying degree of constraint of the lower rating over the higher. A further nine possible matrices were obtained by using a different rule either side of the main axis of the matrix to describe situations where the criteria have a differential influence on the outcome. Uncertainties in the criteria are represented by three alternative frequency distributions from which the assessors select the most appropriate. The output of the utility function is a distribution of rating frequencies that is dependent on the distributions of the input criteria. In pest risk analysis (PRA), seven of these utility functions were required to mimic the logic by which assessors for the European and Mediterranean Plant Protection Organization arrive at an overall rating of pest risk. The framework enables the development of PRAs that are consistent and easy to understand, criticize, compare, and change. When tested in workshops, PRA practitioners thought that the approach accorded with both the logic and the level of resolution that they used in the risk assessments.
© 2013 Society for Risk Analysis.

Keywords:  Bayesian network; decision making; quarantine plant health; risk assessment; risk matrix

Year:  2013        PMID: 23834916     DOI: 10.1111/risa.12089

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  1 in total

1.  Can Public Health Risk Assessment Using Risk Matrices Be Misleading?

Authors:  Shabnam Vatanpour; Steve E Hrudey; Irina Dinu
Journal:  Int J Environ Res Public Health       Date:  2015-08-14       Impact factor: 3.390

  1 in total

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