Personality and safety behavior: An analysis of worldwide research on road and traffic safety leading to organizational and policy implications

This study presents a comprehensive systematic review of worldwide research on the relationship between personality and safety behaviors in context of road and traffic safety to identify key areas, current global trends, and suggest future research direction towards understanding nuances of personality as predictor of accident involvement and risk-taking behaviors. Using bibliometric and visual analysis methods, we examine a sample of 613 studies extracted from the Scopus database based on a search query string with rigorous inclusion and exclusion criteria. Keyword co-occurrence analysis shows five clusters representing focal areas studied by scholars in the field globally which are then classified into central, niche, and emergent themes using the strategic diagram. Further, using citation analysis, co-citation analysis and bibliographic coupling, we highlight the intellectual structure of the knowledge domain and identify potential future areas for research. The results indicate that the research field is yet to be fully developed and more research is warranted towards wider personality traits and subtypes, using different structures of personality, employing longitudinal designs and behavioral methods, and expending insights from personality research for accident prevention and to develop and predict directives for self-driving vehicles. The study concludes by presenting implications for organizations and policymakers.

Automated summary

This study conducts a comprehensive systematic review of research on the relationship between personality and safety behaviors in road and traffic safety. It identifies key areas, current global trends, and suggests future research directions. The results indicate that more research is needed on wider personality traits and subtypes, different structures of personality, longitudinal designs, and behavioral methods. There is also potential to utilize personality research for accident prevention and the development and prediction of self-driving vehicles.