分析灾害管理系统的元网络框架

Chao Fan, Cheng Zhang, A. Mostafavi
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引用次数: 7

摘要

本文的目标是建立一个元网络框架,以识别灾害管理系统(dm - so)中的组成部分,概念化组成部分之间的关系和相互作用,并制定dm - so性能的定量测量,以实现灾害背景下以网络为中心的操作和协调。随着灾害对相互依存和异质性系统的影响日益严重,需要改进有效和综合的灾害响应和协调。然而,现有的一些文献只提出了一些灾害管理系统建模的框架,而另一些研究只考察了社会网络分析(SNA)来理解利益相关者之间的相互作用。因此,缺乏对dm - so的定量和综合测量。为了解决这一知识差距,作者创建并讨论了一个元网络框架,该框架集成了各种类型的实体和关系,用于定量分析dm - so的性能。首先,该框架定义了元度量中的节点和链接,用于抽象灾害管理中的组成部分。其次,创建了一些绩效指标(如有效性、信息共享程度和自组织程度)来显示灾害系统的能力,并利用网络理论转化了灾害环境中的潜在扰动。最后,我们考察了扰动对指标的影响,并通过综合指标来评估绩效。本研究强调了定量测量的重要性,并从综合的角度分析了灾害响应和协调的效率和有效性。该研究还为决策者比较不同的应对策略以实现具有复原力的灾害管理系统提供了启示。
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Meta-Network Framework for Analyzing Disaster Management System-of-Systems
The objective of this paper is to establish a meta-network framework to identify constituents in Disaster Management System-of-Systems (DM-SoS), conceptualize relationships and interactions among the constituents, and formulate quantitative measurements of DM-SoS performance for achieving network-centric operation and coordination in the context of disasters. With increasingly serious impacts of disasters on interdependent and heterogeneous systems, the improvement of effective and integrative disaster response and coordination is needed. However, some existing literature only proposed some frameworks for modeling disaster management systems, while another stream of studies only examined the social network analysis (SNA) for understanding the interactions between stakeholders. Thus, quantitative and integrative measurements in DM-SoS are missing. To address this knowledge gap, the authors created and discussed a meta- network framework integrating various types of entities and relationships for quantitatively analyzing the performance of DM-SoS. First, this framework defined nodes and links in meta-metrics for abstracting constituents in disaster management. Second, some performance indicators (e.g., effectiveness, the extent of information sharing, and the extent of self-organization) were created to show the capacities of disaster systems, and the potential perturbations in disaster environment were translated by network theory. Finally, we examined the impacts of perturbations on the indicators and assessed the performance by integrating overall indicators. This study highlighted the significance of quantitative measurements and an integrative perspective on analyzing efficiency and effectiveness of disaster response and coordination. The study also provides implications for making comparisons of different response strategies for decision makers to achieve resilient disaster management systems.
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