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Cognitive and motivational biases in decision and risk analysis
journal contribution
posted on 2016-06-10, 13:40 authored by Gilberto MontibellerGilberto Montibeller, Detlof von WinterfeldtBehavioral decision research has demonstrated that judgments and decisions of ordinary people and experts are subject to numerous biases. Decision and risk analysis were designed to improve judgments and decisions and to overcome many of these biases. However, when eliciting model components and parameters from decisionmakers or experts, analysts often face the very biases they are trying to help overcome. When these inputs are biased they can seriously reduce the quality of the model and resulting analysis. Some of these biases are due to faulty cognitive processes; some are due to motivations for preferred analysis outcomes. This article identifies the cognitive and motivational biases that are relevant for decision and risk analysis because they can distort analysis inputs and are difficult to correct. We also review and provide guidance about the existing debiasing techniques to overcome these biases. In addition, we describe some biases that are less relevant because they can be corrected by using logic or decomposing the elicitation task. We conclude the article with an agenda for future research.
Funding
Detlof von Winterfeldt acknowledges support from the U.S. Department of Homeland Security (DHS) through the National Center for Risk and Economic Analysis of Terror- ism Events (CREATE) at the University of South- ern California (USC) under award number 2010-ST- 061-RE0001.
History
School
- Business and Economics
Department
- Business
Published in
RISK ANALYSISVolume
35Issue
7Pages
1230 - 1251 (22)Citation
MONTIBELLER, G. and VON WINTERFELDT, D., 2015. Cognitive and motivational biases in decision and risk analysis. Risk Analysis, 35 (7), pp. 1230 - 1251.Publisher
Wiley / © Society for Risk AnalysisVersion
- VoR (Version of Record)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2015Notes
This paper is closed access.ISSN
0272-4332Publisher version
Language
- en