弹性(材料科学)
关键基础设施
过程(计算)
集合(抽象数据类型)
多样性(控制论)
比例(比率)
风险分析(工程)
计算机科学
环境资源管理
业务
管理科学
过程管理
地理
计算机安全
工程类
经济
人工智能
地图学
程序设计语言
物理
操作系统
热力学
作者
Emery Roe,Paul R. Schulman
标识
DOI:10.1080/13876988.2012.664687
摘要
Abstract A major problem in building community resilience in the face of disasters is understanding resilience as an organizational property. A fundamental problem in this understanding is the imbalance in disaster research between the large number of variables and the relatively few cases involved. While resilience is a complex process with many variables at work in determining outcomes, disasters afford far fewer cases with which to compare and understand the multitude of these variables. This is especially true when disasters have a great deal of variety and seldom occur in the same places over the same set of community and organizational variables. Under these conditions it continues to be difficult to isolate causal, much less predictive, factors in resilience. This research has found that far more events challenge resilience in communities and organizations than might be assumed, were one looking only at disasters. In fact organizations can signal their readiness for resilience through measurable responses to far smaller-scale performance challenges. This paper presents a strategy for developing resilience indicators in critical infrastructures that would allow comparative assessment of risks to resilience across infrastructures in different sectors and communities. The strategy is illustrated in resilience indicators developed within one infrastructure, a large and complex high-voltage electrical grid. This strategy is extended and its potential analytic application to additional infrastructures and to the assessment of compound inter-infrastructure reliability is discussed.
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