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Matching Missions to Means: Targeted Resource Allocation in the Non-Profit Sector.
Sommaire Infos
Matching Missions to Means: Targeted Resource Allocation in the Non-Profit Sector.
자료유형  
 학위논문
Control Number  
0017160259
International Standard Book Number  
9798383481868
Dewey Decimal Classification Number  
320.6
Main Entry-Personal Name  
Suresh, Akshaya.
Publication, Distribution, etc. (Imprint  
[S.l.] : Yale University., 2024
Publication, Distribution, etc. (Imprint  
Ann Arbor : ProQuest Dissertations & Theses, 2024
Physical Description  
274 p.
General Note  
Source: Dissertations Abstracts International, Volume: 86-01, Section: B.
General Note  
Advisor: Kaplan, Edward H.
Dissertation Note  
Thesis (Ph.D.)--Yale University, 2024.
Summary, Etc.  
요약This dissertation addresses the challenge of optimizing resource allocation in the non-profit sector. Non-profit organizations have to make real-time decisions that are not only efficient but also equitable. In many cases, new analytic approaches could allow for better informed, data-driven decision-making. Yet, despite their critical role, these organizations often lack the capacity to tap into these tools to increase their impact. This research attempts to bridge this gap through two applications: the identification of students with reading disabilities and the matching of volunteers to organizations. Chapter 2 critiques the current process for diagnosing reading disabilities among students, highlighting the inefficiencies and inequities of the existing system. Drawing on data from a collaboration with the Florida Center for Reading Research, it proposes optimal evaluation policies and improvements to the identification process that could significantly enhance student outcomes by better allocating limited resources within school systems.Chapters 3 and 4 study volunteer labor allocation, using data from VolunteerMatch (VM), a platform connecting non-profits with volunteers. The study identifies VM's imbalanced system-where demand for volunteers often exceeds supply-and the varied sources of traffic to the site. Chapter 3 introduces an improved ranking algorithm, Adaptive Capacity, designed to mitigate this imbalance in the presence of multiple traffic sources, attaining near-optimal theoretical guarantees in some regimes. Chapter 4 assesses the real-world impact of a version of Adaptive Capacity through a series of experiments in Texas and Southern California, employing a difference-in-differences analysis to demonstrate its significant effects on access to volunteers. Through these two collaborations, this dissertation contributes actionable strategies for non-profits to more effectively and equitably manage their limited resources, thereby facilitating more informed decision-making and fostering social good.
Index Term-Uncontrolled  
Matching markets
Index Term-Uncontrolled  
Online platforms
Index Term-Uncontrolled  
Policy evaluation
Index Term-Uncontrolled  
Reading disabilities
Index Term-Uncontrolled  
Sustainable operations
Index Term-Uncontrolled  
Volunteering
Added Entry-Corporate Name  
Yale University Management
Host Item Entry  
Dissertations Abstracts International. 86-01B.
Electronic Location and Access  
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Control Number  
joongbu:654072
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