Closing the Gap Between Decision Analysis and Policy Analysts Before the Next Pandemic

IF 2.5 4区 管理学 Q3 MANAGEMENT Decision Analysis Pub Date : 2023-02-28 DOI:10.1287/deca.2023.0468
R. Dillon, V. Bier, R. S. John, Abdullah Althenayyan
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引用次数: 2

Abstract

Decision analysis (DA) is an explicitly prescriptive discipline that separates beliefs about uncertainties from value preferences in modeling to support decision making. Researchers have been advancing DA tools for the last 60 years to support decision makers handling complex decisions requiring subjective judgments. Recently, some DA researchers and practitioners wondered whether the difficult decisions made during the COVID-19 pandemic regarding testing, masking, closing and reopening businesses, allocating ventilators, and prioritizing vaccines would have been improved with more DA involvement. With its focus on quantifying uncertainties, value trade-offs, and risk attitudes, DA should have been a valuable tool for decision makers during the pandemic. To influence decisions, DA applications require interactions with policymakers and experts to construct formal representations of the decision frame, elicit uncertainties, and assess risk tolerances and trade-offs among competing objectives. Unfortunately, such involvement of decision analysts in the process of decision making and policy setting did not occur during much of the COVID-19 pandemic. This lack of participation may have been partly because many decision makers were unaware of when DA could be valuable in helping with the challenges of the COVID-19 pandemic. In addition, decision analysts were perhaps not sufficiently adept at inserting themselves into the policy process at critical junctures when their expertise could have been helpful. Funding: This research was partially supported by the U.S. Department of Homeland Security through the Center for Accelerating Operational Efficiency at Arizona State University.
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在下一次大流行之前缩小决策分析和政策分析师之间的差距
决策分析(DA)是一门明确的规定性学科,它将建模中的不确定性与价值偏好分离开来,以支持决策制定。在过去的60年里,研究人员一直在推进数据分析工具,以支持决策者处理需要主观判断的复杂决策。最近,一些DA研究人员和从业人员想知道,如果DA更多地参与,在COVID-19大流行期间做出的关于检测、遮盖、关闭和重新开放企业、分配呼吸机和优先接种疫苗的艰难决定是否会得到改善。发展评估侧重于量化不确定性、价值权衡和风险态度,本应成为大流行期间决策者的宝贵工具。为了影响决策,数据分析应用程序需要与决策者和专家进行交互,以构建决策框架的正式表示,引出不确定性,并评估风险容忍度和竞争目标之间的权衡。不幸的是,在COVID-19大流行期间,决策分析人员在决策和政策制定过程中的这种参与并没有发生。缺乏参与的部分原因可能是许多决策者不知道发展援助何时可以在帮助应对COVID-19大流行挑战方面发挥重要作用。此外,决策分析人员也许不善于在他们的专门知识可能有所帮助的关键时刻参与政策过程。资助:本研究部分由美国国土安全部通过亚利桑那州立大学加速运营效率中心提供支持。
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来源期刊
Decision Analysis
Decision Analysis MANAGEMENT-
CiteScore
3.10
自引率
21.10%
发文量
19
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