I-Corps: Dynamic Decision Support for Emergency Managers

通过该项目开发的决策支持软件代表了一种帮助决策者做出明智、有效决策的新工具。该软件工具建立在早期研究的基础上，该研究探索了在管理风险和不确定性时影响信息流的技术系统、组织过程以及物理和社会条件之间的相互作用。设计方法开发实用的决策模型，使用贝叶斯网络和影响图来评估不确定条件，基于系统地识别构成紧急操作环境的技术、组织和知识系统之间的相互依赖关系。它整合了计算机编程和仿真设计方面的技术技能，对商业动态和市场营销的掌握，以及对上下文、政策和应急管理约束的理解。这个决策支持模块根据实际限制和来自多个来源的接近实时的信息，确定可供采取行动的备选方案，并根据经验丰富的应急管理人员的集体判断，计算每个备选方案的成功概率。该决策支持工具解决了信息流过程中的可扩展性和同时性问题，这些问题阻碍了大规模区域灾害中组织间决策的制定。对潜在结果进行建模可以系统地使管理人员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影响。随着全球社会中灾害的数量、类型和严重程度的增加，越来越依赖于运输、发电、通信、天然气、水和废水分配等大规模系统，这些社会技术系统失败的成本和后果呈指数级上升。管理人员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，并调整和适应需求和可用资源之间的平衡，以管理来自极端事件的突然激增的需求。这项技术有可能通过帮助地方政府、非营利组织和小型企业提高管理持续风险的能力来造福社区，同时通过更明智、更有效的决策来减少损失。

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.