Patterns and sources of spatial inequity in freight crashes: An application of decomposition analysis

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6 Scopus citations

Abstract

Despite considerable increases in road freight traffic and associated crashes over the past decade, our understanding of their spatial distribution remains limited. This is concerning because freight vehicle crashes often lead to fatal and severe injuries. This study focuses on Seoul, South Korea and contributes to the literature by investigating the patterns and sources of spatial inequity in freight crashes. Specifically, it examines whether socioeconomically disadvantaged neighborhoods experience a higher concentration of freight crashes. Using the Gelbach's decomposition technique, this study also aims to identify the factors contributing to differences in freight crashes between disadvantaged and less-disadvantaged neighborhoods and quantify their relative contributions. The regression results show that severe freight crashes are more prevalent in disadvantaged neighborhoods before adjusting for other factors—a pattern not observed in non-severe crashes. The decomposition analysis reveals that the observed disparities in severe freight crashes between disadvantaged and less-disadvantaged neighborhoods are fully explained by differences in several neighborhood characteristics, including local road density, truck traffic volume density, proximity to logistics terminals, and off-road bicycle lane density, between neighborhood types. Interestingly, differences in built environment characteristics between neighborhood types not only fail to explain but instead counteract the disparities in severe freight crashes. The findings of this study suggest detailed policy implications for mitigating freight crash occurrences and addressing related spatial inequities.

Original languageEnglish
Article number107683
JournalAccident Analysis and Prevention
Volume205
DOIs
StatePublished - Sep 2024

Keywords

  • Freight crashes
  • Gelbach decomposition technique
  • Neighborhood disadvantage status
  • Road traffic safety
  • Spatial inequity

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