Crime, environments, service characteristics, and transit ridership: a multilevel analysis

Jianling Li (), Qian He () and Qisheng Pan ()
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Jianling Li: University of Texas at Arlington
Qian He: Planning, and Sustainability | Rowan University
Qisheng Pan: University of Texas at Arlington

Transportation, 2025, vol. 52, issue 4, No 7, 1375-1398

Abstract: Abstract Although crime is well recognized as a factor detrimental to ridership, fewer empirical studies have tested the effect of crime on ridership and results are inconclusive. Moreover, existing studies seldom perform multilevel analysis despite using data with a hierarchical structure. This research addresses these gaps using the 2018 data of the five largest cities in the Texas Triangle and multilevel negative binomial regression. The results reveal a non-linear relationship between crime and ridership after controlling for other effects. Transit service characteristics and crime are the top predictors of ridership. The effect of transit trip rate on ridership varies contingent upon crime. The findings have significant implications for research on transit ridership and the improvement of transit services.

Keywords: Transit ridership; Crime; Multilevel negative binomial regression; Forest-based classification and regression; Contextual environments; Service characteristics (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11116-023-10459-0

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