Doctoral Dissertation Research in DRMS: Modeling the Dynamics of Agency-agency Partnerships before and following Extreme Events

本研究的目的是模拟和分析的伙伴关系的创建，长度和结论在网络的机构应对极端事件。研究人员开发模型来探索如何利用伙伴关系的特征来预测机构投资，承诺期限，伙伴关系选择和退出时机的动态。该研究通过采访积极应对极端事件的机构来收集和验证数据。该项目比较了机构在两个独立的灾害响应场景中的行为，在灾害行动期间对机构伙伴关系的生命周期进行数学建模，并进行受控实验来分析机构的决策。在过去几年中，极端事件对世界产生了重大影响，包括地震、海啸、飓风和热带风暴。飓风桑迪、日本地震和海啸以及美国龙卷风等事件的规模和范围，使得我们必须进一步了解政府、非政府组织和商业机构在此类极端事件发生后如何相互作用。本研究建立在应急管理的前期工作的基础上，对极端事件发生后的伙伴关系选择和资源共享过程进行了分析。通过记录极端事件后角色和资源流动的动态变化，这项工作测试了有关机构的假设以及它们如何受到伙伴关系，目标，角色和先前参与的影响。在美国和世界各地积极参与救援行动的许多机构的支持下，对模型结果进行了相关性、准确性和对应对极端事件的机构和个人的正确代表性的检查。

The objective of this research is to model and analyze partnership creation, length, and conclusion in networks of agencies responding to extreme events. The researchers develop models to explore how characteristics of partnerships could be used to predict dynamics in agency investment, commitment length, partnership selection, and exit timing. The research collects and validates data by interviewing agencies active in responding to extreme events. This project compares agency behavior in two separate disaster response scenarios, mathematically models the life-cycle of agency partnerships during disaster operations, and conducts controlled experiments to analyze agency decision making. Extreme events have had a significant impact on the world over the last several years, including earthquakes, tsunamis, hurricanes, and tropical storms. The scale and scope of events like Hurricane Sandy, the earthquake and tsunami in Japan, and the tornados around the United States make it imperative to increase our understanding of how government, non-governmental, and business agencies interact with one another in the aftermath of such extreme events. This study builds on previous work in emergency management to provide an analysis of the partnership selection and resource sharing processes that occur following an extreme event. By documenting the dynamical change in roles and flow of resources following extreme events, this work tests hypotheses regarding agencies and how they are impacted by partnerships, goals, roles, and prior involvement. With the support of a host of agencies that are actively involved in relief operations in the U.S. and around the world, the model results are checked for relevance, accuracy, and correct representation of the agencies and individuals responding to extreme events.