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

Autor: Holt J; Natural Resources Institute, University of Greenwich, Chatham Maritime, Kent, ME4 4TB, UK.; Centre for Environmental Policy, Imperial College London, Silwood Park, Ascot SL5 7PY, UK., Leach AW; Centre for Environmental Policy, Imperial College London, Silwood Park, Ascot SL5 7PY, UK., Schrader G; Julius Kühn Institute, Federal Research Centre for Cultivated Plants, Messeweg 11-12 38104, Braunschweig, Germany., Petter F; European and Mediterranean Plant Protection Organisation, 21, boulevard Richard Lenoir, 75011, Paris, France., MacLeod A; The Food and Environment Research Agency, Sand Hutton, York, YO41 1LZ, UK., van der Gaag DJ; Office for Risk Assessment and Research, Netherlands Food and Consumer Product Safety Authority, Utrecht, the Netherlands., Baker RH; The Food and Environment Research Agency, Sand Hutton, York, YO41 1LZ, UK., Mumford JD; Centre for Environmental Policy, Imperial College London, Silwood Park, Ascot SL5 7PY, UK.
Jazyk: angličtina
Zdroj: Risk analysis : an official publication of the Society for Risk Analysis [Risk Anal] 2014 Jan; Vol. 34 (1), pp. 4-16. Date of Electronic Publication: 2013 Jul 08.
DOI: 10.1111/risa.12089
Abstrakt: 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.)
Databáze: MEDLINE
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