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<p>The present study aims to identify the underlying reasons for speeding behavior among young drivers on inter-city roads. A novel hybrid method, BWQM, is proposed by integrating the Best–Worst Method (BWM) as a multi-criteria decision-making technique with Q methodology (QM) as a psychological sorting approach. The BWQM offers policymakers a structured tool to assess the psychological determinants of risky driving behavior. A key advantage of BWQM is its ability to address the cognitive complexity associated with Q-sorting by enabling systematic prioritization of statements. Thirty-eight statements, derived from a comprehensive literature review, were categorized into five categories: Personal Beliefs, Social Factors, Regulatory Factors, Situational Factors, and Environmental Factors. The analysis was conducted using expert judgment data collected from 30 experienced traffic police officers, who provided insights into the behavioral and psychological factors contributing to young drivers’ speeding. Within the BWQM framework, the BWM was applied to facilitate structured prioritization of factors by experts, enhancing the rigor and consistency of the Q-methodological analysis. These expert-derived perspectives were formalized into Q-cards and subjected to factor analysis. Three distinct viewpoints were identified, accounting for 67.5% of the cumulative variance. The results indicate that, from the experts’ perspective, preventive measures—such as higher fines for violations, speed cameras, and an increased police presence —are the most effective strategies for mitigating speeding behavior among young drivers.</p>

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An expert-based psychological analysis of young drivers' speeding behavior using a novel hybrid decision-making method (BWQM)

  • 期刊论文

  • 发表日期：

    2025年10月2日

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  • Seyedreza Seyedalizadeh Ganji,
  • Ali Nasrollahtabar Ahangar

摘要

The present study aims to identify the underlying reasons for speeding behavior among young drivers on inter-city roads. A novel hybrid method, BWQM, is proposed by integrating the Best–Worst Method (BWM) as a multi-criteria decision-making technique with Q methodology (QM) as a psychological sorting approach. The BWQM offers policymakers a structured tool to assess the psychological determinants of risky driving behavior. A key advantage of BWQM is its ability to address the cognitive complexity associated with Q-sorting by enabling systematic prioritization of statements. Thirty-eight statements, derived from a comprehensive literature review, were categorized into five categories: Personal Beliefs, Social Factors, Regulatory Factors, Situational Factors, and Environmental Factors. The analysis was conducted using expert judgment data collected from 30 experienced traffic police officers, who provided insights into the behavioral and psychological factors contributing to young drivers’ speeding. Within the BWQM framework, the BWM was applied to facilitate structured prioritization of factors by experts, enhancing the rigor and consistency of the Q-methodological analysis. These expert-derived perspectives were formalized into Q-cards and subjected to factor analysis. Three distinct viewpoints were identified, accounting for 67.5% of the cumulative variance. The results indicate that, from the experts’ perspective, preventive measures—such as higher fines for violations, speed cameras, and an increased police presence —are the most effective strategies for mitigating speeding behavior among young drivers.