Date of Award
Spring 2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Management
First Advisor
Kaplan, Edward
Abstract
This 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.
Recommended Citation
Suresh, Akshaya, "Matching Missions to Means: Targeted Resource Allocation in the Non-Profit Sector" (2024). Yale Graduate School of Arts and Sciences Dissertations. 1380.
https://elischolar.library.yale.edu/gsas_dissertations/1380
