Analysis of a driving behavior measurement model using a modified driver behavior questionnaire encompassing texting, social media use, and drug and alcohol consumption

Thailand is a leading country in terms of road crash statistics in the World Health Organization South-East Asia region. Several factors have been identified in relation to such crashes, including humans, vehicles, and the environment, of which the human factor constitutes the largest ratio (90%–95%...

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Bibliographic Details
Main Authors: Sajjakaj Jomnonkwao, Savalee Uttra, Vatanavongs Ratanavaraha
Format: Article
Language:English
Published: Elsevier 2021-03-01
Series:Transportation Research Interdisciplinary Perspectives
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2590198221000063
Description
Summary:Thailand is a leading country in terms of road crash statistics in the World Health Organization South-East Asia region. Several factors have been identified in relation to such crashes, including humans, vehicles, and the environment, of which the human factor constitutes the largest ratio (90%–95%). This study aims to create a measurement model of driving behaviors in Thailand. A driver behavior questionnaire (DBQ) was integrated with data on texting and social media-related driver behaviors. In addition, we observed behaviors such as drug and alcohol consumption while driving. The participants consisted of 1532 adults 20 years of age or older with a driving license from 30 provinces in Thailand. Confirmatory factor analysis was used to develop the measurement model. The findings come from 25 questions from the DBQ and five questions about new additional behaviors in the model. The factors used for the measurement of driving behaviors concern violations, errors, lapses, and aggressiveness. Moreover, the modified DBQ regarding texting and social media, as well as drug and alcohol consumption, was used for the measurement of driving behaviors as well. The questionnaire can be used to measure Thai drivers’ behaviors and meet the goodness-of-fit statistics criteria of every measurement model and develop self-assessment reports to evaluate risky behaviors before people obtain a driving license. Moreover, this research contributes to the literature by introducing a model for improvements in road safety policies to support current laws and to reduce risky behaviors such as driving after alcohol consumption and texting while driving.
ISSN:2590-1982