Experiment on the Information Integration of Risk Perception of Drunk Driving

• Main Authors: Wen-Chun Kuo, 郭文俊
• Other Authors: Ming-Shen Wang
• Format: Others
• Language: zh-TW
• Published: 2001
• Online Access: http://ndltd.ncl.edu.tw/handle/89363898957044528240

碩士 === 國立中山大學 === 公共事務管理研究所 === 89 === Over the past five years, an average of about 323 traffic accidents that were caused by drunk driving occurred in Taiwan every year, resulting in 306 deaths and injuring 297 people and costing Taiwan society a lot. Concerned government agencies have recognized this harsh problem and taken measures as a counteract, for example, imposing heavy fines and punishing the driver with penal code, in order to discourage this poor habit of drunk driving. However, the tragedies caused by drunk driving have not abated. Government agencies usually execute public powers from the subjective perspective of statutory law, and similarly the research and investigation of related problems conducted in Taiwan usually emphasize the enforcement aspect. However, the results of foreign research indicate that risk message can be conveyed through risk communication so as to change the public’s risk perception, resulting in their changes in behavior. This study began with the cognitive perspective of the risk of drunk driving perceived by the law enforcers, voluntary group of drunk driving risk, and pressured group of drunk driving risk, and used the experimental method of Information Integration Theory to investigate the integrated algebra model of each concerned group’s “probability information” and “outcome information” of drunk driving risk and its level of risk perception. The findings are as follows: I. Cognitive algebra model (I) On drunk driving cases with high-probability, low-outcome risk of being stopped, the law enforcers as a whole used the multiplying model, while the drunk driving group and the ordinary driving group used the equal-weight averaging model to integrate the information. (II) On drunk driving cases with low-probability, high-outcome risk of causing traffic accidents, the law enforcers, the drunk driving group, and the ordinary group all used the adding model, with more emphasis on the outcome information. (III) On drunk driving cases with high-probability, low-outcome risk of being stopped, most people used the equal-weight averaging model, and they used the adding model on the cases of low-probability, high-outcome risk of causing traffic accidents. II. Risk perception (I) The drunk driving group had the highest risk perception on the type of high-probability, low-outcome risk of being stopped drunk driving, the ordinary group had the second highest risk perception, and the law enforcers had the lowest risk perception. (II) The ordinary group had the highest risk perception on the type of low-probability, high-outcome risk of drunk driving causing traffic accidents, the drunk driving group had the second highest risk perception, and the law enforcers had the lowest risk perception.