A Comparison of Contributing Factors between Young and Old Riders of Motorcycle Crash Severity on Local Roads

Thanapong Champahom (), Chamroeun Se, Sajjakaj Jomnonkwao, Tassana Boonyoo and Vatanavongs Ratanavaraha
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Thanapong Champahom: Department of Management, Faculty of Business Administration, Rajamangala University of Technology Isan, Nakhon Ratchasima 30000, Thailand
Chamroeun Se: School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
Sajjakaj Jomnonkwao: School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
Tassana Boonyoo: Traffic and Transport Development and Research Center (TDRC), King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand
Vatanavongs Ratanavaraha: School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand

Sustainability, 2023, vol. 15, issue 3, 1-24

Abstract: This study aims to identify the factors that influence the severity of motorcycle crashes on local roads, particularly given the high speeds often observed for motorcycles on these roads with low traffic volumes and numerous multi-leg intersections. Previous research has shown that a rider’s age can impact their speed behavior. To explore this issue, data on motorcycle crashes from 2015 to 2020 in Thailand—a middle-income developing country—were analyzed using a random parameter logit model with unobserved heterogeneity in means and variances, comparing young (<30-year-old) and older (>50-year-old) riders. The contributing factors were divided into four groups: driver, crash, environmental, and road factors. The transferability test yielded different results for the young rider and old rider models, indicating that it is appropriate to analyze these models separately. A constant value revealed that old riders were more likely to die in a crash than young riders. In terms of the random parameter, the local address and road surface variables were found to be significant in both models. The results of unobserved heterogeneity in means and variances identified significant variables in both models, including gender, exceeding the speed limit, lit roads, unlit roads, mobile phone use, and road surface. These findings were used to develop policy recommendations for reducing the severity of motorcycle crashes on local roads.

Keywords: crash fatality; developing country; rider age; unobserved heterogeneity; random parameter logit model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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