CAREER: Public-Sector Decision Modeling for Facility Location and Service Delivery

该项目将制定规范性规划模式，以解决两个重要问题：为低收入家庭提供补贴住房和为老年人提供社会服务。这些应用领域很重要，因为这两类服务的接受者通常被认为是社会最应得到的"，但实际上，在提供这些服务时很少或根本没有使用定量规划方法，而这种方法在交通、医药、应急和警察服务以及环境等其他领域已经很普遍。此外，由于缺乏以下方面的知识，很难对这两种类型的服务提供进行主动规划：预测服务需求；衡量可选政策的美元价值和非美元价值的影响，并选择平衡效率，公平和有效性的竞争关注的政策。在这个项目中使用的主要分析工具是：基于运筹学/管理科学（OR/MS）的优化规划模型，以在有限的资源和特定目标下产生政策选择；城市经济模型，以确定住房和劳动力市场的特征，并确定各种补贴住房的潜在配置的影响；基于统计和地理信息系统（GIS）的预测模型，以估计老年人服务的需求，以及群体谈判和决策，以确定最优先的政策来实施。本项目将对定量公共政策研究和教学做出重要贡献。首先，可以综合评估资助住房选址和提供养老服务的收益和成本。其次，它将能够设计有效的策略来解决与这两个领域相关的困难优化问题。第三，通过使用实际机构数据，研究人员和政策制定者可能会相信，与目前的做法相比，这些规划模型可以提高服务提供的质量。第四，它将为设计和实施资助房屋选址和提供安老服务的多利益相关者决策支持系统（DSS）提供框架。最后，它将使学校和公共政策及公共行政学系能更有效地推动理科/管理学和资讯系统/资讯科技（IS/ it）课程的开设，并使这些课程更顺利地融入传统课程。这个项目的重要性更大，因为它产生的模型将帮助那些管理或倡导补贴住房和老年人服务提供的人更好地证明可能看起来有争议的政策举措是合理的，至少在短期内是这样。在补贴住房和老年人服务提供方面产生的许多政治争议的特点是：关于当前情况的数据不完整，无法确定与其他潜在政策举措相关的现实结果，以及在谈判达成所有各方都能接受的单一政策替代方案方面存在很大困难。这项学术研究并不是为了将政策分析师或政治活动家转变为or /MS或is /IT方面的专家，也不会消除围绕公共部门设施位置和服务提供这些方面的模糊性和不确定性。然而，这项研究可能会说服政策和政治辩论中的一些参与者，与传统的政策分析和政治倡导方法相比，总体上使用规划模型，以及更准确的数据估计和明确定义的方法来讨论政策选择，可能会产生社会更好的结果。最后，这项研究将使公共政策和公共管理专业的学生能够更容易地利用基于OR/MS和IS/IT的定量规划和实施工具，商学院毕业生多年来一直使用这些工具来提高私营部门组织的效率。

This project will develop prescriptive planning models to addresses two important problems: provision of subsidized housing for low-income families and social services for the elderly. These application areas are important because the recipients of these two types of services are usually considered society's most deserving", yet in practice these services are delivered with little or no use of quantitative planning methodologies that have become common in other domains, such as transportation, medicine, emergency and police services and the environment. Moreover, proactive planning for these two types of service delivery is difficult due to the lack of knowledge regarding: forecasting of demand for services; measuring dollar-valued and non-dollar-valued impacts of alternative policies, and choosing policies that balance competing concerns of efficiency, equity and effectiveness. Key analytical tools to be used in this project are: optimization-based planning models from operations research/management science (OR/MS) to generate policy alternatives given limited resources and specific objectives; urban economic models to characterize housing and labor markets and to identify impacts of various potential configurations of subsidized housing; forecasting models based on statistics and geographic information systems (GIS) to estimate demands for senior services, and group negotiations and decisionmaking to identify most-preferred policies to implement. This project will result in a number of important contributions to quantitative public policy research and teaching. First, it will enable the comprehensive evaluation of benefits and costs of subsidized housing location and elderly service provision. Second, it will enable the design of efficient strategies for solving difficult optimization problems associated with these two domains. Third, through use of actual agency data, researchers and policymakers may be persuaded that these planning models could improve the quality of service provision as compared to current practice. Fourth, it will provide a framework for the design and implementation of multiple-stakeholder decision support systems (DSS) for subsidized housing location and elderly service provision. Last, it will enable schools and departments of public policy and public administration to better motivate course offerings in MS/OR and information systems/information technology (IS/IT), and to integrate these course more smoothly into traditional curricula.This project is important more generally because the models it generates will help those who manage or advocate for subsidized housing and elderly service delivery to better justify policy initiatives that may seem controversial, at least in the short run. Many of the political controversies arising in subsidized housing and elderly service delivery are characterized by: incomplete data on current conditions, an inability to identify realistic outcomes associated with alternative potential policy initiatives, and great difficulty in negotiating towards a single policy alternative acceptable to all parties. This academic research is not intended to transform policy analysts or political activists into experts in OR/MS or IS/IT, nor will it eliminate ambiguity and uncertainty surrounding these facets of public-sector facility location and service delivery. However, the research may persuade some actors in policy and political debates that the use of planning models in general, along with more accurate data estimates and well-defined ways to discuss policy alternatives, could result in outcomes in which society is better off as compared to traditional policy-analytic and political advocacy methods. Finally, this research will enable students of public policy and public administration to more readily avail themselves of OR/MS- and IS/IT- based quantitative planning and implementation tools that business school graduates have used for years to improve the efficiency of private-sector organizations.