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首页> 外文期刊>Technological forecasting and social change >Robust decision making and Epoch-Era analysis: A comparison of two robustness frameworks for decision-making under uncertainty
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Robust decision making and Epoch-Era analysis: A comparison of two robustness frameworks for decision-making under uncertainty

机译：强大的决策和epoch-era分析：在不确定性下决策两种鲁棒性框架的比较

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摘要

Several model-based frameworks have been introduced in support of robust decision-making. While they agree on a need to cope with uncertainty for robust inferences, the frameworks differ in the way that they treat uncertainty and obtain decision insights. In this article, we compare and contrast two such frameworks: Robust Decision Making and Epoch-Era Analysis. We critically analyse the two frameworks in terms of their aims and expected decision insights, the way they cope with uncertainty, and the extent to which they use model-based and participatory analysis. Our conceptual comparison sheds light on the strengths and limitations of the two frameworks in different contexts. We then apply both frameworks to an illustrative case to analyse their benefits and caveats in practice. We conclude that the superiority of each framework is not unconditional, and depends on the context and the problem at hand. While Robust Decision Making is a more effective framework under contested and imprecise information about the future, Epoch-Era Analysis can work better when stakeholder knowledge about the future allows a deliberative specification of future scenarios. The evaluation of both frameworks' strengths and limitations can contribute to future methodological developments in the literature on decision-making under uncertainty.
机译：已经引入了一些基于模型的框架，以支持强大的决策。虽然他们一致认为需要应对强劲推理的不确定性，但框架在他们对待不确定性并获得决策洞察力的方式方面不同。在本文中，我们比较和对比两种这样的框架：强大的决策和epoch-era分析。我们根据其目标和预期决策洞察力来批判地分析了两个框架，他们应对不确定性的方式，以及他们使用基于模型和参与性分析的程度。我们的概念比较阐明了不同背景下两个框架的优势和局限性。然后，我们将两个框架应用于一个说明性案例，以分析他们的利益和练习。我们得出结论，每个框架的优越性不是无条件的，并取决于上下文和手头的问题。虽然强大的决策是关于未来的有争议和不精确的信息的更有效的框架，但在利益相关者的知识允许审慎规范的情况下，EPOCH-ERA分析可以更好地工作。对框架的优势和局限性的评估可以有助于在不确定性下决策的文献中的未来方法论。

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