Cognitive and Motivational Biases in Decision and Risk Analysis
Cognitive and Motivational Biases in Decision and Risk Analysis
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DOI：
10.1111/risa.12360
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发表时间：
2015-07-01
期刊：
影响因子：
3.8
通讯作者：
von Winterfeldt, Detlof
中科院分区：
文献类型：
--
作者：
Montibeller, Gilberto;von Winterfeldt, Detlof
行为决策研究表明，普通人和专家的判断和决策受到许多偏见的影响。决策和风险分析旨在改善判断和决策，并克服许多这些偏见。然而，当从决策者或专家那里获得模型组件和参数时，分析师往往面临着他们试图帮助克服的偏见。当这些输入有偏差时，它们会严重降低模型和结果分析的质量。其中一些偏差是由于错误的认知过程;一些是由于偏好分析结果的动机。这篇文章识别了与决策和风险分析相关的认知和动机偏见，因为它们会扭曲分析输入，并且难以纠正。我们还审查和现有的去偏置技术，以克服这些偏见提供指导。此外，我们还描述了一些不太相关的偏见，因为它们可以通过使用逻辑或分解启发任务来纠正。最后，我们对未来的研究议程的文章。
Behavioral 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.