東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Decision Analysis in Public Policy: ...

Watlington, Victoria.

FindBook

Google Book

Amazon

博客來

Decision Analysis in Public Policy: Multi-Objective Optimization for Economic Mobility Policy Portfolio Mix in Local Urban Governments.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Decision Analysis in Public Policy: Multi-Objective Optimization for Economic Mobility Policy Portfolio Mix in Local Urban Governments./
作者:	Watlington, Victoria.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
面頁冊數:	253 p.
附註:	Source: Dissertations Abstracts International, Volume: 85-02, Section: B.
Contained By:	Dissertations Abstracts International85-02B.
標題:	Public policy. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30630875
ISBN:	9798380077521

Decision Analysis in Public Policy: Multi-Objective Optimization for Economic Mobility Policy Portfolio Mix in Local Urban Governments.
Watlington, Victoria.

Decision Analysis in Public Policy: Multi-Objective Optimization for Economic Mobility Policy Portfolio Mix in Local Urban Governments. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 253 p.

Source: Dissertations Abstracts International, Volume: 85-02, Section: B.

Thesis (Ph.D.)--The University of North Carolina at Charlotte, 2023.

This item must not be sold to any third party vendors.

In this dissertation, I take an interdisciplinary approach to improve the budget allocation process for economic mobility policy by leveraging multi-objective optimization as a decision support tool. Economic mobility is measured as the difference in income between Black and White populations, known as the racial wealth gap. Lack of quantitative data linking budget policy selections to mobility metrics hinders government efficiency and the effectiveness of public investment. I propose a novel application of multi-objective optimization1 to identify optimal mixes aimed at increasing economic mobility in urban cities, restoring rational comprehensive decision making to the process, reducing government waste and improving resident outcomes.The optimization model is the main contribution of my research to both the systems engineering and public policy fields. The first of its kind, it is the basis for a practical decision support tool that can be utilized to help cities determine where to direct funding for greater gains in economic mobility. It also enables cities to select true peer cities from which to benchmark, assess return on investment at various levels of spending, and identify potential private partners based on additional investment needs to achieve community aims.The results indicate that each of the above factors plays a role in the level of aid that a city receives, and how that aid is spent. I found that while these factors do impact spending choices, budget policy alone does not drive economic mobility outcomes.

ISBN: 9798380077521Subjects--Topical Terms:

532803
Public policy.
Subjects--Index Terms:

Budget

Decision Analysis in Public Policy: Multi-Objective Optimization for Economic Mobility Policy Portfolio Mix in Local Urban Governments.
LDR:02887nmm a2200409 4500 001 2396891
005 20240618081811.5
006 m o d
007 cr#unu||||||||
008 251215s2023 ||||||||||||||||| ||eng d
020 $a 9798380077521
035 $a (MiAaPQ)AAI30630875
035 $a AAI30630875
040 $a MiAaPQ $c MiAaPQ
100 1 $a Watlington, Victoria. $3 3766644
245 1 0 $a Decision Analysis in Public Policy: Multi-Objective Optimization for Economic Mobility Policy Portfolio Mix in Local Urban Governments.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2023
300 $a 253 p.
500 $a Source: Dissertations Abstracts International, Volume: 85-02, Section: B.
500 $a Includes supplementary digital materials.
500 $a Advisor: Windett, Jason.
502 $a Thesis (Ph.D.)--The University of North Carolina at Charlotte, 2023.
506 $a This item must not be sold to any third party vendors.
520 $a In this dissertation, I take an interdisciplinary approach to improve the budget allocation process for economic mobility policy by leveraging multi-objective optimization as a decision support tool. Economic mobility is measured as the difference in income between Black and White populations, known as the racial wealth gap. Lack of quantitative data linking budget policy selections to mobility metrics hinders government efficiency and the effectiveness of public investment. I propose a novel application of multi-objective optimization1 to identify optimal mixes aimed at increasing economic mobility in urban cities, restoring rational comprehensive decision making to the process, reducing government waste and improving resident outcomes.The optimization model is the main contribution of my research to both the systems engineering and public policy fields. The first of its kind, it is the basis for a practical decision support tool that can be utilized to help cities determine where to direct funding for greater gains in economic mobility. It also enables cities to select true peer cities from which to benchmark, assess return on investment at various levels of spending, and identify potential private partners based on additional investment needs to achieve community aims.The results indicate that each of the above factors plays a role in the level of aid that a city receives, and how that aid is spent. I found that while these factors do impact spending choices, budget policy alone does not drive economic mobility outcomes.
590 $a School code: 0694.
650 4 $a Public policy. $3 532803
650 4 $a Systems science. $3 3168411
653 $a Budget
653 $a Cities
653 $a Economic mobility
653 $a Optimization
653 $a Urban government
690 $a 0630
690 $a 0790
690 $a 0501
710 2 $a The University of North Carolina at Charlotte. $b Infrastructure & Environmental Systems. $3 3180175
773 0 $t Dissertations Abstracts International $g 85-02B.
790 $a 0694
791 $a Ph.D.
792 $a 2023
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30630875