@article{ref1,
title="Inequity analysis of spatial mismatch for low-income socially vulnerable populations across America",
journal="Transportation research part D: transport and environment",
year="2023",
author="Ermagun, Alireza and Janatabadi, Fatemeh and Maharjan, Sanju",
volume="118",
number="",
pages="e103692-e103692",
abstract="This study examines the extent to which public transit contributes to the spatial mismatch between low-income households and the gap between low- and high-wage employment and searches for social inequity in the transit-related spatial mismatch across the 50 most populated American metropolitan areas. Wage Gap (WG) and Transit Access Wage Gap (TAWG) measures are proposed to calculate the disparity between low- and high-wage employment and transit access to low- and high-wage employment opportunities. The Bivariate Local Indicator of Spatial Autocorrelation (BiLISA) identifies areas where low-income households experience spatial mismatch due to (i) employment location and (ii) transit access service. Two findings are obtained.First, transit acts as a catalyst for separating low-income households from low-wage employment. Second, the transit-related spatial mismatch disproportionately discriminates and impacts socially vulnerable populations, particularly African Americans and carless households.<p /> <p>Language: en</p>",
language="en",
issn="1361-9209",
doi="10.1016/j.trd.2023.103692",
url="http://dx.doi.org/10.1016/j.trd.2023.103692"
}