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

CAREER: Public-Sector Decision Modeling for Facility Location and Service Delivery
职业:公共部门设施选址和服务交付决策建模
批准号:
0134890
负责人:
Michael Johnson
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-08-01 至 2008-07-31

项目摘要

项目成果

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中文摘要
翻译
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上最应得的“,但在实践中,这些服务的提供很少或根本没有使用在交通、医疗、紧急情况和警察服务以及环境等其他领域中普遍使用的量化规划方法。此外,由于缺乏以下方面的知识,很难对这两类服务的提供进行积极主动的规划:预测服务需求;衡量替代政策的美元价值和非美元价值的影响;以及选择平衡效率、公平和效力等相互矛盾的关切的政策。该项目将使用的主要分析工具包括:运筹学/管理科学(OR/MS)的基于优化的规划模型,以在有限资源和特定目标的情况下生成政策备选方案;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,以估计对高级服务的需求;以及小组谈判和决策,以确定最优先实施的政策。该项目将对量化公共政策研究和教学做出一些重要贡献。首先,它将使人们能够全面评估资助住房选址和提供老人服务的效益和成本。其次,它将使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,通过使用实际的机构数据,研究人员和政策制定者可能会被说服,与当前的做法相比,这些规划模型可以提高服务提供的质量。第四,它将为设计和实施多利益攸关方决策支持系统(DSS)提供一个框架,以提供补贴住房选址和老年服务。最后,它将使学校和公共政策和公共行政部门能够更好地推动MS/OR和信息系统/信息技术(IS/IT)课程的提供,并将这些课程更顺利地整合到传统课程中。这个项目更重要,因为它产生的模式将帮助那些管理或倡导提供补贴住房和老年服务的人更好地证明可能存在争议的政策举措的合理性,至少在短期内是这样。在补贴住房和老年服务提供方面出现的许多政治争议的特点是:关于当前状况的数据不完整,无法确定与其他潜在政策举措相关的现实结果,以及在谈判达成各方都能接受的单一政策替代方案方面存在极大困难。这项学术研究的目的并不是将政策分析员或政治活动家转变为运筹学/管理系统或信息系统/信息技术领域的专家,也不会消除围绕公共部门设施选址和服务提供这些方面的模棱两可和不确定性。然而,这项研究可能会说服政策和政治辩论中的一些行为者,总体上使用规划模型,加上更准确的数据估计和讨论政策替代方案的明确方式,可能会产生与传统的政策分析和政治倡导方法相比,社会状况更好的结果。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的量化规划和实施工具,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。
英文摘要
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.
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Collaborative Research: Experimental General Relativity using Radio Interferometry of a Black Hole Photon Ring
Carbon Fibre Axle (CaFiAx)
  • 批准号:
    EP/X038254/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $64.54万
  • 财政年份:
    2023
  • 负责人:
    Michael Johnson
  • 依托单位:
REU Site: The National Summer Undergraduate Research Project
  • 批准号:
    2149582
  • 项目类别:
    Standard Grant
  • 资助金额:
    $93.54万
  • 财政年份:
    2022
  • 负责人:
    Michael Johnson
  • 依托单位:
Online Undergraduate Resource Fair for the Advancement and Alliance of Marginalized Mathematicians
  • 批准号:
    2230388
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.0万
  • 财政年份:
    2022
  • 负责人:
    Michael Johnson
  • 依托单位:
海外基金