I-Corps: Dynamic Decision Support for Emergency Managers

通过该项目开发的决策支持软件是一种新的工具，可以帮助决策者做出明智、有效的决策。该软件工具建立在早期研究的基础上，这些研究探索了在管理风险和不确定性方面影响信息流的技术系统、组织流程以及物理和社会条件之间的相互作用。该设计方法使用贝叶斯网络和影响图来开发实用的决策模型，以评估不确定条件，基于对表征紧急操作环境的组件技术、组织和知识系统之间的相互依赖关系的系统识别。它结合了计算机编程和模拟设计的技术技能，掌握了业务动态和营销，以及对应急管理的背景、政策和约束的理解。该决策支持模块根据实际限制和来自多个来源的近乎实时的信息，确定可供采取行动的选项，并根据经验丰富的应急管理人员的集体判断，计算每个选项的成功概率。这一决策支持工具解决了在大规模地区性灾难中阻碍组织间决策的信息流过程中的可扩展性和同时性问题。对潜在结果进行建模可以系统地使管理者能够比较更广泛的选择。如果开发成功，这种动态决策支持工具可能会对社区管理风险的方式产生变革性的影响。随着灾害的数量、类型和严重程度的增加，在一个日益依赖运输、发电、通信以及天然气、水和废水分配的大规模系统的全球社会，这些社会技术系统发生故障的成本和后果呈指数级上升。管理者可能需要改进的工具来同时监控这些相互依赖的操作系统，并调整和调整需求和可用资源之间的平衡，以管理极端事件导致的需求突然激增。这项技术有可能帮助地方政府、非营利组织和小企业提高管理其持续风险敞口的能力，并通过更知情、更有效的决策来减少损失，从而使社区受益。

The decision support software developed through this project represents a new tool to aid decision makers in making informed, efficient decisions. The software tool builds on earlier research that explored interactions among technical systems, organizational processes, and physical and social conditions that affect information flow in managing risk and uncertainty. The design approach develops practical decision models using Bayesian networks and influence diagrams to assess uncertain conditions, based on systematic identification of interdependencies among the component technical, organizational, and knowledge systems that characterize urgent operating environments. It integrates technical skills in computer programming and simulation design, grasp of business dynamics and marketing, and understanding of context, policies, and constraints of emergency management. This decision support module identifies options available for action, given actual constraints and near-real time information from multiple sources, and calculates the probability of success of each option, based on the collective judgment of experienced emergency managers. This decision support tool addresses problems of scalability and simultaneity in information flow processes that have hindered inter-organizational decision making in large-scale, regional disasters. Modeling potential outcomes can systematically enable managers to compare a broader range of options. If successfully developed, this dynamic decision support tool may have a transformative effect on how communities manage risk. As the number, type, and severity of disasters increase in a global society that depends increasingly on large-scale systems in transportation, power generation, communication, and gas, water and wastewater distribution, the cost and consequences of failure in these socio-technical systems escalate exponentially. Managers may need improved tools to monitor these interdependent operating systems simultaneously, and adjust and adapt the balance between demand and resources available to manage sudden surges in demand from extreme events. This technology has the potential to benefit communities through helping local governments, nonprofit organizations, and small businesses increase their capacity to manage their continuing exposure to risk, but reduce losses by more informed, effective decision making.