An investigation of the effects of motorcycle-riding experience on aberrant driving behaviors and road traffic accidents-A case study of Pakistan
DOI: 10.1080/13588265.2020.1774479
archive: archived pipeline: cataloged verified
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Summary
This study investigates the impact of motorcycle-riding experience on aberrant driving behaviors and road traffic accidents (RTAs) among vehicle drivers in Pakistan, a country with high motorcycle usage and alarming RTA rates. The research is motivated by the hypothesis that aberrant riding behaviors, such as improper U-turns and reckless overtaking, may be memorized and transferred to vehicle driving, thereby increasing accident risk. Given the lack of prior research linking motorcycle experience to vehicle driving behaviors in developing nations, this study aims to identify specific behavioral factors and their relationship with RTAs. The researchers conducted a self-reported web-based questionnaire survey in Pakistan from February to March 2018, collecting 396 valid responses from drivers. The survey utilized a newly designed 23-item Driver Behavior Questionnaire (DBQ) to measure aberrant driving behaviors, alongside questions on demographic characteristics, motorcycle-riding experience, and self-reported RTA history over the previous three years. Statistical analyses included Principal Component Analysis (PCA) to identify behavioral factors, Spearman correlation analysis, Proportional Odds (PO) models to assess the influence of motorcycle experience on behaviors, and binary logistic regression to examine the link between behaviors and RTAs. PCA revealed a three-factor structure of aberrant driving behaviors: self-willed violations/errors, distracted violations, and risky violations/errors. The PO model results indicated that motorcycle-riding experience significantly influenced distracted violations but had no significant effect on self-willed or risky violations/errors. Specifically, drivers with no motorcycle experience or limited experience (1–3 years) exhibited higher rates of distracted violations compared to those with extensive experience (>20 years). Demographic factors also played a role; for instance, higher income and education levels were associated with fewer violations, while single and male drivers reported more distracted violations. Crucially, the study found no direct statistical relationship between motorcycle-riding experience and RTA involvement. However, a significant association was identified between distracted violations and RTAs, with a one-unit increase in distracted violations raising the probability of being involved in an RTA by 54%. The findings suggest that while motorcycle-riding experience does not directly cause accidents, it influences specific aberrant behaviors, particularly distracted violations. The strong link between distracted violations and RTAs highlights distraction as a critical risk factor in Pakistan’s traffic safety landscape. These results provide a new perspective on how motorcycle use connects to vehicle driving behaviors, offering valuable insights for targeted interventions aimed at reducing RTAs by addressing distracted driving rather than focusing solely on general riding experience.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-24 |
| archive | success | semantic_scholar | — | — | 6 | 2026-06-26 |
| extract | success | pdftotext | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-26 |
| chunk | success | chunk | — | — | 1 | 2026-06-26 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-26 |
| enrich | success | openalex | — | — | 1 | 2026-06-26 |
| promote | success | — | — | — | 1 | 2026-06-24 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-26 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
Topics
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- sex gender
- cultural cross national
- novice drivers
- human error taxonomy
- motorcyclist skill
- dbq psychometrics
Information type
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- Empirical Findings: observational prevalence, behavioral performance data
- Theoretical Contribution: computational model