Mapping Urban Infrastructure: Temporal Metropolitan Geographies of Nonprofit Human Service Organizations

Loading...
Thumbnail Image
Degree type
Master of City and Regional Planning (MCRP)
Graduate group
Discipline
Subject
nonprofit
human services
poverty
spatial analysis
linear regression modeling
Urban, Community and Regional Planning
Funder
Grant number
License
Copyright date
Distributor
Related resources
Author
Massey, Sarah Nicole
Contributor
Abstract

Across the United States, planning for human services relies largely upon public-private partnerships with nonprofit organizations as the result of decades of federal retrenchment. The locational patterns of nonprofit human services organizations (NHSOs) have been studied in the nonprofit literature, but there is little scholarship on this topic in the realm of city planning. This research connects these two disciplines while answering two questions: 1) Where do NHSOs cluster over time within metropolitan statistical areas (MSAs)? 2) Are NHSOs locating in response to community needs, resources, or conditions? In order to establish generalizable results across space and time, this study used a multi-site analysis of eight MSAs in 2010 and 2018: Austin, TX; Buffalo, NY; Cleveland, OH; Indianapolis, IN; Philadelphia, PA; Research Triangle, NC; Sacramento, CA; and Seattle, WA. Two quantitative methods explored these questions. First, a spatial analysis used density-based clustering to identify clusters of NHSOs throughout each MSA. Then linear regression modeling revealed relationships between the NHSO landscape and various socioeconomic and built environment variables. The results of this analysis demonstrated evidence of NHSO clustering that warrants further investigation. Furthermore, the evidence confirmed previous findings that NHSO patterns are more related to resources and community conditions than need. While this study contributes to a growing body of research in the nonprofit field, there are theoretical frameworks, practical tools, and policy solutions that should prompt city planners to take interest in this subject as well.

Advisor
Reina, Vincent
Ammon, Francesca Russello
Date of degree
2022-05-01
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
Concentration: Public Private Development
Recommended citation