TY - JOUR
T1 - Decomposing neighborhood disparities in bicycle crashes
T2 - A Gelbach decomposition analysis
AU - Shin, Eun Jin
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2023/2
Y1 - 2023/2
N2 - Despite growing evidence showing significant spatial disparities in bicycle crash rates within a city, little research has explored their contributing factors. Focusing on Seoul, South Korea, this study examines whether differences in bicycle crash rates between neighborhoods with low and high socioeconomic status (SES) exist, and if so, which and to what extent the observable neighborhood characteristics explain them. This study adopts the Gelbach decomposition method to illuminate the sources of bicycle crash disparities between neighborhoods with different SES. Results indicate that bicycle crashes are more likely to occur in low-SES neighborhoods, regardless of injury severity. However, contrary to popular expectations, the differences in bicycle infrastructure or bicycle traffic volume between high- and low-SES neighborhoods do not significantly contribute to the gaps in bicycle crash outcomes between neighborhood types. Instead, the differences in population density and road networks based on neighborhood SES are the primary drivers of these gaps. Another notable finding is that the neighborhood-level factors included in the analysis can altogether explain less than 50% of the disparities in bicycle crashes between neighborhood types. The findings of this study provide valuable policy suggestions that help address spatial equity related to bicycle crashes.
AB - Despite growing evidence showing significant spatial disparities in bicycle crash rates within a city, little research has explored their contributing factors. Focusing on Seoul, South Korea, this study examines whether differences in bicycle crash rates between neighborhoods with low and high socioeconomic status (SES) exist, and if so, which and to what extent the observable neighborhood characteristics explain them. This study adopts the Gelbach decomposition method to illuminate the sources of bicycle crash disparities between neighborhoods with different SES. Results indicate that bicycle crashes are more likely to occur in low-SES neighborhoods, regardless of injury severity. However, contrary to popular expectations, the differences in bicycle infrastructure or bicycle traffic volume between high- and low-SES neighborhoods do not significantly contribute to the gaps in bicycle crash outcomes between neighborhood types. Instead, the differences in population density and road networks based on neighborhood SES are the primary drivers of these gaps. Another notable finding is that the neighborhood-level factors included in the analysis can altogether explain less than 50% of the disparities in bicycle crashes between neighborhood types. The findings of this study provide valuable policy suggestions that help address spatial equity related to bicycle crashes.
KW - Bicycle crash
KW - Decomposition analysis
KW - Neighborhood disparity
KW - Socioeconomic status
KW - Spatial equity
UR - https://www.scopus.com/pages/publications/85144437691
U2 - 10.1016/j.tranpol.2022.12.014
DO - 10.1016/j.tranpol.2022.12.014
M3 - Article
AN - SCOPUS:85144437691
SN - 0967-070X
VL - 131
SP - 156
EP - 172
JO - Transport Policy
JF - Transport Policy
ER -