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Matching Missions to Means: Targeted Resource Allocation in the Non-Profit Sector.
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
- 로그인을 한후 보실 수 있는 자료입니다.
- Control Number
- joongbu:654072
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