{"title":"司机为何抵制使用部分自动化功能?从心理反应理论的角度看问题","authors":"Yiran Zhang, Heming Gong, Chundong Zheng","doi":"10.1016/j.trf.2024.09.007","DOIUrl":null,"url":null,"abstract":"<div><p>Autonomous vehicles equipped with automation driving assistance features are attracting significant public attention for their safety, innovation, and efficiency. While existing research has explored how individuals’ cognition of autonomous vehicles influences their acceptance or adoption intention, there is limited understanding of drivers’ post-purchase usage behavior, particularly their resistance to using automation features. Taking the lens of psychological reactance theory, this research investigates the impact of driver type and car class on resistance to using automation features. We conducted a survey (N=391) and found that drivers with limited experience exhibit higher resistance to using these features compared to experienced drivers. This effect is mediated by the perceived threat to driving freedom and is moderated by car class. Specifically, this effect only holds for economy cars but not high-end cars. Our findings can help managers develop personalized recommendations for consumers regarding autonomous vehicles, and provide a reference for designing driver assistance systems tailored to car class.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 383-394"},"PeriodicalIF":3.5000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Why do drivers resist the use of partial automation features? A perspective from psychological reactance theory\",\"authors\":\"Yiran Zhang, Heming Gong, Chundong Zheng\",\"doi\":\"10.1016/j.trf.2024.09.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Autonomous vehicles equipped with automation driving assistance features are attracting significant public attention for their safety, innovation, and efficiency. While existing research has explored how individuals’ cognition of autonomous vehicles influences their acceptance or adoption intention, there is limited understanding of drivers’ post-purchase usage behavior, particularly their resistance to using automation features. Taking the lens of psychological reactance theory, this research investigates the impact of driver type and car class on resistance to using automation features. We conducted a survey (N=391) and found that drivers with limited experience exhibit higher resistance to using these features compared to experienced drivers. This effect is mediated by the perceived threat to driving freedom and is moderated by car class. Specifically, this effect only holds for economy cars but not high-end cars. Our findings can help managers develop personalized recommendations for consumers regarding autonomous vehicles, and provide a reference for designing driver assistance systems tailored to car class.</p></div>\",\"PeriodicalId\":48355,\"journal\":{\"name\":\"Transportation Research Part F-Traffic Psychology and Behaviour\",\"volume\":\"107 \",\"pages\":\"Pages 383-394\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part F-Traffic Psychology and Behaviour\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1369847824002584\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part F-Traffic Psychology and Behaviour","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1369847824002584","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, APPLIED","Score":null,"Total":0}
Why do drivers resist the use of partial automation features? A perspective from psychological reactance theory
Autonomous vehicles equipped with automation driving assistance features are attracting significant public attention for their safety, innovation, and efficiency. While existing research has explored how individuals’ cognition of autonomous vehicles influences their acceptance or adoption intention, there is limited understanding of drivers’ post-purchase usage behavior, particularly their resistance to using automation features. Taking the lens of psychological reactance theory, this research investigates the impact of driver type and car class on resistance to using automation features. We conducted a survey (N=391) and found that drivers with limited experience exhibit higher resistance to using these features compared to experienced drivers. This effect is mediated by the perceived threat to driving freedom and is moderated by car class. Specifically, this effect only holds for economy cars but not high-end cars. Our findings can help managers develop personalized recommendations for consumers regarding autonomous vehicles, and provide a reference for designing driver assistance systems tailored to car class.
期刊介绍:
Transportation Research Part F: Traffic Psychology and Behaviour focuses on the behavioural and psychological aspects of traffic and transport. The aim of the journal is to enhance theory development, improve the quality of empirical studies and to stimulate the application of research findings in practice. TRF provides a focus and a means of communication for the considerable amount of research activities that are now being carried out in this field. The journal provides a forum for transportation researchers, psychologists, ergonomists, engineers and policy-makers with an interest in traffic and transport psychology.