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Abstract：
Decision Support Systems (DSS) have emerged as important tools for enhancing community resilience due to their ability to provide timely and efficient solutions to disaster-related problems while reflecting the perspectives of different stakeholders and utilizing multiple data sources. This paper provides a comprehensive summary of DSS applications to community resilience, emphasizing how the different modeling techniques are used in different disaster phases. We found that optimization techniques are the most frequently used methods for building DSS. Furthermore, we found that DSS tend to focus more on the preparedness and response phases of disaster management, rather than the recovery and mitigation phases. Moreover, the study highlights the main challenges in developing and implementing DSS for resilience, such as data availability, the uncertainty of the disaster context, and the need for cross-disciplinary collaboration. Based on the reviewed papers, we provide some guidelines to practitioners to select the most suitable decision-support tools for the needs of their community. The study aims to help decision-makers and researchers build effective decision support systems for enhancing community resilience, considering the current challenges.
摘要：
决策支持系统（DSS）已成为增强社区复原力的重要工具，因为它们能够为灾难相关问题提供及时有效的解决方案，同时反映不同利益相关者的观点并利用多种数据源。本文全面总结了DSS在社区弹性中的应用，强调如何在不同的灾害阶段使用不同的建模技术。我们发现优化技术是构建DSS最常用的方法。此外，我们发现DSS倾向于更多地关注灾难管理的准备和响应阶段，而不是恢复和缓解阶段。此外，这项研究强调了开发和实施复原力DSS的主要挑战，例如数据可用性，灾难背景的不确定性，以及跨学科合作的需要。根据审查的论文，我们为从业人员提供一些指导方针，以选择最适合其社区需求的决策支持工具。该研究旨在帮助决策者和研究人员建立有效的决策支持系统，以增强社区的适应力，考虑到当前的挑战。
