This study investigates the impact of warning message phrasing on drivers’ speeding behavior in the Chinese context through a simulated driving experiment. It focuses on the effects of sentence structure (declarative vs. rhetorical) and word choice (suggestive vs. controlling) while incorporating gender, driving style, and speeding experience as covariates. The results reveal that rhetorical questions evoke negative emotions and heightened threat perceptions in drivers, resulting in less effective persuasion. Controlling language, although more persuasive, induces stronger negative emotional responses. Therefore, we recommend avoiding rhetorical questions in Chinese warning messages, adopting more tactful expressions, and flexibly using controlling language based on urgency to enhance decision-making efficiency. This research provides theoretical support for optimizing the design of traffic warning messages and offers new perspectives for traffic safety management and behavioral interventions.

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The Impact of Warning Message Phrasing on Drivers’ Speeding Decisions in the Chinese Context

  • Mengyan Shen,
  • Chaomin Ma,
  • Shan Zhong,
  • Fanrui Zeng,
  • Hao Tan

摘要

This study investigates the impact of warning message phrasing on drivers’ speeding behavior in the Chinese context through a simulated driving experiment. It focuses on the effects of sentence structure (declarative vs. rhetorical) and word choice (suggestive vs. controlling) while incorporating gender, driving style, and speeding experience as covariates. The results reveal that rhetorical questions evoke negative emotions and heightened threat perceptions in drivers, resulting in less effective persuasion. Controlling language, although more persuasive, induces stronger negative emotional responses. Therefore, we recommend avoiding rhetorical questions in Chinese warning messages, adopting more tactful expressions, and flexibly using controlling language based on urgency to enhance decision-making efficiency. This research provides theoretical support for optimizing the design of traffic warning messages and offers new perspectives for traffic safety management and behavioral interventions.