Pedestrians' intention to jaywalk: Automatic or planned? A study based on a dual-process model in China

Area of Science:

• Psychology
• Traffic Safety
• Behavioral Science

Background:

• Understanding pedestrian traffic law violations is crucial for urban safety.
• Existing models often focus on cognitive factors, potentially overlooking automatic processes.
• A dual-process model offers a framework to examine both controlled and automatic influences on behavior.

Purpose of the Study:

• To investigate the determinants of Chinese pedestrians' intention to violate traffic laws.
• To apply a dual-process model, integrating controlled (Theory of Planned Behavior) and automatic (past behavior) processes.
• To identify which factors most significantly predict traffic violation intention.

Main Methods:

• A survey was conducted with 323 adult pedestrian respondents in China.
• The study utilized an augmented Theory of Planned Behavior (TPB) framework.
• Relative weight analysis was employed to determine the predictive importance of different factors.

Main Results:

• Personal norms significantly predicted traffic violation intention.
• Descriptive norms were not significant predictors of intention.
• Past behavior emerged as the strongest predictor, explaining 42% of the variance in intention.

Conclusions:

• Pedestrians' intention to violate traffic laws is predominantly driven by automatic processes (habit) rather than controlled cognitive factors or social norms.
• Intervention programs should consider habit formation and modification strategies.
• Findings highlight the importance of incorporating dual-process models in traffic safety research.