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Decision making under deep uncertainties: A review of the applicability of methods in practice

机译:深度不确定性的决策:审查实践中方法的适用性

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摘要

Deep uncertainties like environmental and socio-economic changes create challenges to decision making. Decision Making under Deep Uncertainty (DMDU) methods are recognised approaches to navigate deep uncertainties and support robust and adaptable decisions. However, their ability to fully reflect the context in which these decisions are made has been criticised. This paper presents a synthesis across cases and methods to provide a holistic understanding of the application of DMDU methods to support long-term decision making. We carried out a structured literature review and analysed 37 infrastructure DMDU case studies. The analysis shows that DMDU methods are effective at developing plans to address a range of deep uncertainties and in some cases, reflecting the institutional context of the decision. However, they largely overlook the organisational and individual contexts in which decision making happens. We argue that the use of existing DMDU methods in practice should start with a better understanding of the institutional, organisational and individual contexts. We then suggest modifications to the applications of DMDU methods, i.e. internalising the context at different stages of the decision-making process and developing a decision typology to signpost decision makers to the best approach for a specific context.
机译:像环境和社会经济变革的深度不确定性会对决策产生挑战。在深度不确定性(DMDU)方法下的决策是识别的方法,以导航深度不确定性和支持强大和适应性决策。然而,他们充分反映了这些决定的背景的能力受到批评。本文介绍了对案例和方法的合成,以提供对DMDU方法支持长期决策的应用的全面了解。我们进行了结构化文献综述,并分析了37个基础设施DMDU案例研究。分析表明,DMDU方法在制定计划以解决一系列深度不确定性的计划中是有效的,并在某些情况下反映出决定的制度范围。但是,它们在很大程度上忽略了决策发生的组织和个人环境。我们认为,在实践中使用现有的DMDU方法应该从更好地了解制度,组织和个别背景。然后,我们建议对DMDU方法的应用的修改,即在决策过程的不同阶段内部内部化,并制定决策类型,以指导决策者以获得特定背景的最佳方法。

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