Student Theses
Date of Award
Spring 5-29-2026
Document Type
Thesis
Language
English
First Advisor
Dr. Arthur O’Connor
Abstract
This study examines structural mobility access across New York City census tracts by constructing a tract-level Mobility Access Index (MAI) that integrates employment accessibility, hospital accessibility, and first-mile subway walking burden using MTA GTFS transit data, NYC Taxi and Limousine Commission trip records, and US Census American Community Survey demographic estimates. Three OLS regression models, supplemented by Lasso, Elastic Net, and Random Forest specifications, test whether structural access gaps are associated with short-distance connector trip intensity and per-worker connector cost burden. Results show that MAI varies substantially across tracts, with high access concentrated in Manhattan and along major subway corridors. Lower structural access is modestly associated with greater connector trip reliance and is more strongly associated with higher per-worker connector cost burden. An exploratory interaction suggests that this burden falls disproportionately on lower-income neighborhoods, consistent with transport justice concerns regarding the uneven distribution of mobility costs.
Recommended Citation
Cruz, John, "Transportation Deserts and Structural Mobility Access in New York City" (2026). CUNY Academic Works.
https://academicworks.cuny.edu/sps_etds/5
Included in
Data Science Commons, Infrastructure Commons, Public Policy Commons, Social Justice Commons, Social Statistics Commons, Social Welfare Commons, Statistics and Probability Commons, Transportation Commons, Urban Studies Commons, Urban Studies and Planning Commons
Comments
City University of New York (CUNY) - School of Professional Studies
Master of Science in Data Science
DATA 698 - Analytics Master's Research
May 2026