Volume List  / Volume 3 (2)



DOI: 10.7708/ijtte.2013.3(2).06

3 / 2 / 173-184 Pages


Rosemary R. Seva - Human Factors and Ergonomics Center, Industrial Engineering Department, De La Salle University, 2401 Taft Avenue, Malate, Manila -

Glaiza Marie T. Flores - Human Factors and Ergonomics Center, Industrial Engineering Department, De La Salle University, 2401 Taft Avenue, Malate, Manila -

Maria Patricia T. Gotohio - Human Factors and Ergonomics Center, Industrial Engineering Department, De La Salle University, 2401 Taft Avenue, Malate, Manila -

Noel Gabriel C. Paras - Human Factors and Ergonomics Center, Industrial Engineering Department, De La Salle University, 2401 Taft Avenue, Malate, Manila -


The study aims to determine significant personal and environmental variables in predicting motorcycle accidents in the Philippines, compare the results with findings in other countries, and propose possible government interventions. Data were gathered from 177 participants through the use of a survey in a licensing center in the largest city in Metro Manila. Logistic regression was used to predict the likelihood of an accident from variables considered in the model. Three variables were found to be significant predictors of motorcycle accidents: age, driving behavior, and junction type. Younger drivers are more likely to be involved in accidents. The significance of age was unexpected because similar models found this to be insignificant. Driving behavior, specifically, committing violation predicts accident likelihood. Driving at t- and y-junctions also predicts motorcycle accidents. In the Philippines, a unique set of variables were found to predict motorcycle accidents. Although previous studies have established the effect of these variables to accident likelihood, the combination was unforeseen. Government agencies can focus on interventions directed at these three variables.

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