Collaborative Research: An Interdisciplinary Approach to Modeling Multiple Stakeholder Decision-Making to Reduce Regional Natural Disaster Risk

自然灾害给美国带来了巨大的损失。尽管几十年来私营部门和公共政策做出了许多努力，但目前的自然灾害风险管理系统对政府、保险业或房主来说并不是很有效。以前的研究已经产生了很多关于个人和组织如何做出与风险相关的决策，个体保险公司和保险市场作为一个整体的战略行为，以及自然灾害风险本身和物理减少它的方法的知识。然而，理解不同参与群体或利益相关者的选择如何作为一个系统相互作用的努力？都是有限的。拟议的项目将产生一个相互作用的数学模型的新框架，可用于更好地理解、设计和评估政府的自然灾害风险管理政策，例如提供资金帮助房主加固房屋，要求房主购买自然灾害保险，或提供购买高风险房屋。通过支持改进公共政策的设计和评估，该项目将帮助该国更好地管理其风险。通过预先考虑个人的，有时是相互竞争的利益相关者的观点，作为分析的一个组成部分，新的框架将更容易确定那些最有可能付诸行动并有效的双赢的全系统解决方案。该框架被设计为与？整个社区吗?联邦紧急事务管理局（FEMA）提倡的办法，鼓励社区各方面参与帮助应对这一挑战。在项目开始时，让相关政府机构、保险和住宅建筑行业的代表作为合作伙伴，将有助于确保研究提供可用的结果，并能尽快有效地付诸实践。研究生和本科生的研究助理，包括女性和未被充分代表的少数民族，将参与这项研究，研究人员将把研究结果纳入他们的课程和他们大学的新博士项目中。该项目将在理解美国自然灾害风险管理系统的整体行为方面取得飞跃，从而有助于提供改进该系统所需的知识。为了实现这些好处，我们建议开发一个新的框架，将包括五个相互作用的数学模型？(1)政府决定引入哪些法规和/或提供哪些激励措施，(2)保险公司决定收取哪些保险费用和购买哪些再保险，(3)保险公司之间的竞争，(4)个人房主决定是否购买保险和/或加固房屋，以及(5)区域自然灾害损失的模型。它将利用现有的第一版框架，其中包括相互作用的保险公司-房主和损失模型，但将通过以下五个任务对这一努力进行实质性改进：(1)确定房主决策类型的类别和基于描述房主在现实生活中如何实际做出这些决策的数据的房主决策模型；(2)扩展框架以包括决策和信息随时间变化的方式；(3)包括利益相关者没有完美或相同信息的情况；(4)开发和纳入政府决策模型；(5)在北卡罗来纳州住宅飓风风险的全面案例研究中展示了该框架。

Natural disasters create enormous costs for the United States. Despite many private sector and public policy efforts over decades, the current system of managing natural disaster risk is not working well for the government, the insurance industry, or homeowners. Previous research has resulted in a lot of knowledge about how individuals and organizations make risk-related decisions, the strategic behavior of individual insurers and the insurance market as a whole, as well as natural disaster risk itself and ways to physically reduce it. Nevertheless, efforts to understand how the choices of the different participating groups or stakeholders interact as a ?system? have been limited. The proposed project will result in a new framework of interacting mathematical models that can be used to better understand, design, and evaluate government natural disaster risk management policies, such as providing funds to help homeowners strengthen their homes, requiring homeowners to buy natural disaster insurance, or offering to buy high-risk homes. By supporting improved design and evaluation of public policies, the project will help the country better manage its risk. By considering the individual, sometimes competing stakeholder points-of-view up front, as an integral part of the analysis, the new framework will make it easier to identify those win-win system-wide solutions that are most likely to be put into action and to be effective. The framework is designed to be consistent with the ?whole community? approach promoted by the Federal Emergency Management Agency (FEMA), which encourages involving all parts of the community in helping to address the challenge. Engaging representatives of the relevant government agencies and insurance and home building industries as partners at the beginning of the project will help ensure that the research offers usable results that can be put into practice as quickly and effectively as possible. Graduate and undergraduate research assistants, including women and underrepresented minorities, will participate in the research, and the researchers will incorporate the results into their courses and new Ph.D. programs at their universities. The project will result in a leap forward in understanding the overall behavior of the natural disaster risk management system in the U.S., thus helping provide the knowledge needed to improve it.To achieve these benefits, we propose to develop a new framework that will include five interacting mathematical models?models of (1) government decisions about what regulations to introduce and/or incentives to offer, and (2) insurer decisions about what to charge for insurance policies and what reinsurance to buy, (3) competition among insurers, (4) individual homeowner decisions about whether to buy insurance and/or strengthen their homes, and (5) regional natural disaster losses. It will make use of an existing first version of the framework that includes interacting insurer-homeowner and loss models but will improve on that effort substantially through five tasks: (1) identifying categories of homeowner decision types and a homeowner decision model that is based on data describing how homeowners actually make these decisions in real life, (2) extending the framework to include the way decisions and information change over time, (3) including situations in which the stakeholders do not have perfect or the same information, (4) developing and incorporating a model of government decisions, and (5) demonstrating the framework in a full-scale case study applied to residential hurricane risk in North Carolina.