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Journal Article

Citation

Se C, Champahom T, Jomnonkwao S, Kronprasert N, Ratanavaraha V. Anal. Meth. Accid. Res. 2022; 36: e100240.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.amar.2022.100240

PMID

unavailable

Abstract

This paper examines the differences between weekday, weekend, and holiday crashes on the severity of motorcyclist injury using four-year motorcycle crash data in Thailand from 2016 to 2019. While also considering the temporal stability assessment of significant factors, this study adopted a random parameters logit model with possible heterogeneity in means and variances to account for unobserved heterogeneity. Three levels of motorcyclist injury severity were considered including minor injury, severe injury, and fatal injury. Two series of likelihood ratio tests clearly indicated nontransferability between weekday, weekend, and holiday crashes and substantial temporal instability over the four-year study period.

FINDINGS also revealed many statistically significant factors that affect motorcyclist injury severity probabilities in various time-of-year and yearly models. In addition, the prediction comparison results (using out-of-sample prediction simulation) clearly illustrated substantial differences between weekday, weekend, and holiday motorcyclist injury severity probabilities, and substantial changes in each injury predicted probabilities over time. This paper highlights the importance of accounting for day-of-week and holiday transferability and temporal instability with unobserved effects in the determinants that affect motorcyclist injury severity. Through the observed nontransferability and temporal instability, the findings provide valuable knowledge for practitioners, researchers, institutions, and decision-makers to enhance highway safety, specifically motorcyclist safety, and facilitate the development of more effective motorcycle crash injury mitigation policies.


Language: en

Keywords

Developing country; Motorcyclist safety; Random-parameter logit model; Unobserved heterogeneity

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