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The Role of Big Five Personality Traits in Explaining Pedestrian Anger Expression

Author

Listed:
  • Kayvan Aghabayk

    (School of Civil Engineering, College of Engineering, University of Tehran, Tehran 4563-11155, Iran)

  • Sina Rejali

    (School of Civil Engineering, College of Engineering, University of Tehran, Tehran 4563-11155, Iran)

  • Nirajan Shiwakoti

    (School of Engineering, RMIT University, Melbourne 3000, Australia)

Abstract

Although the relationship between anger and personality characteristics in the literature is well-acknowledged for drivers, there is a lack of systematic investigation of pedestrians. The current study aimed to evaluate pedestrian anger expression (PAX) and its contributing factors, including demographics, travel habits, and the big five personality traits. To test the effects of different variables on PAX scales, data from 742 respondents were collected. The data were analyzed through a two-stage approach of clustering and a logistic regression model. Participants were clustered into two groups of low expression and high expression based on their responses to PAX items. An exploratory factor analysis identified significant constructs of PAX, including “Adaptive/Constructive Expression”, “Anger Expression-In”, and “Anger Expression-out”. It was found that males were more likely to show high anger expressions. Public transport usage and previous crash involvement could significantly increase the probability of high anger expression. On the other hand, life satisfaction and intention to avoid traffic were negatively associated with high anger expression. The results revealed that neuroticism, extraversion, and openness to experience could positively contribute to higher anger expression; however, agreeableness and conscientiousness were negatively associated with high anger expression for pedestrians.

Suggested Citation

  • Kayvan Aghabayk & Sina Rejali & Nirajan Shiwakoti, 2022. "The Role of Big Five Personality Traits in Explaining Pedestrian Anger Expression," Sustainability, MDPI, vol. 14(19), pages 1-10, September.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12099-:d:924355
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    Cited by:

    1. Mohammed Abdullah Ammer & Zeyad A. T. Ahmed & Saleh Nagi Alsubari & Theyazn H. H. Aldhyani & Shahab Ahmad Almaaytah, 2023. "Application of Artificial Intelligence for Better Investment in Human Capital," Mathematics, MDPI, vol. 11(3), pages 1-17, January.

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