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Are objectives hierarchy related biases observed in practice? A meta-analysis of environmental and energy applications of Multi-Criteria Decision Analysis

机译:在实践中是否观察到与目标层次相关的偏见?多标准决策分析在环境和能源应用中的元分析

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摘要

Procedural and behavioural biases have received little attention in recent Multi-Criteria Decision Analysis (MCDA) research. Our literature review shows that most research on biases was done 15–30 years ago. This study focuses on biases that are introduced at an early stage of MCDA when building objectives hierarchies and their effect on the weights. The main objective is to investigate whether prior findings regarding such biases, which were mostly based on laboratory experiments, can be found in real-world applications. We conducted a meta-analysis of the objectives hierarchies and weight elicitation procedures in 61 environmental and energy MCDA cases. Relationships between the structural characteristics of the objectives hierarchy and assigned objectives’ weights were analysed with statistical tests. Our main research questions were: (i) How does hierarchy size and structure affect the objectives’ weights? (ii) How are weights distributed across economic, social and environmental objectives? (iii) Is there support for the equalising bias? Our findings are mostly aligned with earlier research and suggest that the hierarchy structure and content can substantially influence weight distributions. For example, hierarchical weighting seems to be sensitive to the asymmetry bias, which can occur when a hierarchy has branches that differ in the number of sub-objectives. We found no evidence for the equalising bias. We highlight issues deserving more attention when developing objectives hierarchies and eliciting weights. The research demonstrates the potential to use meta-analysis, which has not previously been used in this way in the MCDA field, to learn from a collection of applications.
机译:程序和行为偏差在最近的多标准决策分析(MCDA)研究中很少受到关注。我们的文献综述表明,大多数关于偏见的研究都是在15至30年前完成的。这项研究的重点是在建立目标层次结构及其对权重的影响时,在MCDA早期引入的偏见。主要目的是研究在实际应用中是否可以找到主要基于实验室实验的有关此类偏差的先前发现。我们对61个环境和能源MCDA案例中的目标层次结构和权重确定过程进行了荟萃分析。使用统计测试分析了目标层次结构的结构特征与分配的目标权重之间的关系。我们的主要研究问题是:(i)层次结构的大小和结构如何影响目标的权重? (ii)如何在经济,社会和环境目标之间分配权重? (iii)是否支持均衡偏见?我们的发现大部分与早期研究相吻合,并表明层次结构和内容会严重影响体重分布。例如,层次结构加权似乎对不对称偏差敏感,当层次结构的子对象数目不同时,这种不对称偏差就会发生。我们没有找到均衡偏见的证据。我们着重指出在制定目标层次结构和得出权重时应引起更多关注的问题。研究表明,有可能使用元分析(从以前在MCDA领域中尚未以这种方式使用)来从一系列应用程序中学习。

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