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首页> 外文期刊>Risk analysis >Workforce/Population, Economy, Infrastructure, Geography, Hierarchy, and Time (WEIGHT): Reflections on the Plural Dimensions of Disaster Resilience
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Workforce/Population, Economy, Infrastructure, Geography, Hierarchy, and Time (WEIGHT): Reflections on the Plural Dimensions of Disaster Resilience

机译：劳动力/人口，经济，基础设施，地理，层次结构和时间（权重）：对灾难复原力的多个方面的思考

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The concept of resilience and its relevance to disaster risk management has increasingly gained attention in recent years. It is common for risk and resilience studies to model system recovery by analyzing a single or aggregated measure of performance, such as economic output or system functionality. However, the history of past disasters and recent risk literature suggest that a single-dimension view of relevant systems is not only insufficient, but can compromise the ability to manage risk for these systems. In this article, we explore how multiple dimensions influence the ability for complex systems to function and effectively recover after a disaster. In particular, we compile evidence from the many competing resilience perspectives to identify the most critical resilience dimensions across several academic disciplines, applications, and disaster events. The findings demonstrate the need for a conceptual framework that decomposes resilience into six primary dimensions: workforce/population, economy, infrastructure, geography, hierarchy, and time (WEIGHT). These dimensions are not typically addressed holistically in the literature; often they are either modeled independently or in piecemeal combinations. The current research is the first to provide a comprehensive discussion of each resilience dimension and discuss how these dimensions can be integrated into a cohesive framework, suggesting that no single dimension is sufficient for a holistic analysis of a disaster risk management. Through this article, we also aim to spark discussions among researchers and policymakers to develop a multicriteria decision framework for evaluating the efficacy of resilience strategies. Furthermore, the WEIGHT dimensions may also be used to motivate the generation of new approaches for data analytics of resilience-related knowledge bases.
机译：弹性概念及其与灾害风险管理的相关性近年来越来越受到关注。风险和弹性研究通常通过分析单个或总体性能指标（例如经济产出或系统功能）来对系统恢复进行建模。但是，过去灾难的历史和最近的风险文献表明，对相关系统的一维视图不仅不够，而且会损害管理这些系统的风险的能力。在本文中，我们探讨了多维因素如何影响复杂系统在灾难后运行和有效恢复的能力。特别是，我们从许多竞争的弹性角度汇编证据，以确定跨多个学科，应用和灾难事件的最关键的弹性维度。研究结果表明，需要一个将弹性分解为六个主要维度的概念框架：劳动力/人口，经济，基础设施，地理，等级和时间（权重）。这些维度在文献中通常没有完整地论述。通常，它们要么是独立建模，要么是零碎组合。当前的研究是第一个对每个弹性维度进行全面讨论并讨论如何将这些维度整合到一个有凝聚力的框架中的研究，这表明没有单一的维度足以对灾难风险管理进行整体分析。通过本文，我们还旨在引发研究人员和决策者之间的讨论，以开发用于评估弹性策略功效的多准则决策框架。此外，WEIGHT维度还可以用于激励新方法的产生，以进行与弹性相关的知识库的数据分析。

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