Meta-analysis of driving behavior studies and assessment of factors using structural equation modeling

Abstract

The aim of this paper is to understand the factors that influence unsafe driving practices by examining published studies that utilized the theory of planned behavior (TPB) to predict driving behavior. To this end, 42 studies published up to the end of 2021 are reviewed to evaluate the predictive utility of TPB by employing a meta-analysis and structural equation model. The results indicate that these studies sought to predict 20 distinct driving behaviors (e.g., drink-driving, use of cellphone while driving, aggressive driving) using the original TPB constructs and 43 additional variables. The TPB model with the three original constructs is found to account for 32% intentional variance and 34% behavioral variance. Among the 43 variables researchers have examined in TPB studies related to driving behavior, this study identified the six that are commonly used to enhance the TPB model’s predictive power. These variables are past behavior, self-identity, descriptive norm, anticipated regret, risk perception, and moral norm. When past behavior is added to the original TPB model, it increases the explained variance in intention to 52%. When all six factors are added to the original TPB model, the best model has only four variables (perceived risk, self-identity, descriptive norm, and moral norm); and increases the explained variance to 48%. The influence of the TPB constructs on intention is modified by behavior category and traffic category. The findings of this paper validate the application of TPB to predicting driving behavior. It is the first study to do this through the use of meta-analysis and structural equation modeling.

Keywords

• Theory of planned behavior
• Driving intention
• Driving behavior
• Traffic violation
• Meta-analysis
• Structural Equation Modeling