{"title":"Intention of the utilization of rearview mirrors: integrating TPB and TTF models to explore factors among Chinese electric bike users.","authors":"Kang Jiang, Wanlin Chen, Qingqing Deng, Dongdong Shi, Zhenhua Yu, Zhipeng Huang, Xiaojiao Chen","doi":"10.1080/15389588.2025.2466839","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Considering the value of rearview mirrors in providing essential rear visual information to electric bike (e-bike) users, this study aims to analyze the psychological traits influencing users' willingness and behavior toward rearview mirror usage and to understand their decision-making processes. Combined the Theory of Planned Behavior (TPB) and Task Technology Fit (TTF), and introduced the extended variable of perceived danger, this study explores the psychological factors that shape e-bike users' willingness and behavior regarding rearview mirror usage from a social psychology perspective.</p><p><strong>Methods: </strong>A questionnaire survey was conducted on e-bike users (<i>N</i> = 704) in China. The data collected included demographic characteristics, components integrated the TPB and TTF, and relevant extended variables. Structural equation analysis (SEM) was used to analyze the data, as well as demographic variable analysis.</p><p><strong>Results: </strong>The integration of the TPB and TTF models provides an effective framework for explaining and predicting the behavior and intentions of Chinese e-bike users regarding rearview mirror usage. The results of the model show that rearview mirrors fit e-bikes riding task, attitudes toward rearview mirror usage, and e-bike users characteristics associated with rearview mirror use increase e-bike users' willingness to use rearview mirrors. The extended TPB construct of perceived risk did not emerge as a formidable predictor in the e-bike riders' adoption of rearview mirrors. Additionally, results from multiple-group SEM analysis of four demographic variables (age, gender, e-bike riding experience, rearview mirror usage experience) suggest significant differences among e-bike users in using rearview mirrors while riding on the road.</p><p><strong>Conclusions: </strong>This study establishes the validity of the integrated model of TPB and TTF model in predicting the use of rearview mirrors by e-bike users. Furthermore, the current findings may provide theoretical support for developing intervention strategies to promote rearview mirror usage, safety education initiatives, and the design improvements of rearview mirrors for e-bikes users.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-9"},"PeriodicalIF":1.6000,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Traffic Injury Prevention","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/15389588.2025.2466839","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Considering the value of rearview mirrors in providing essential rear visual information to electric bike (e-bike) users, this study aims to analyze the psychological traits influencing users' willingness and behavior toward rearview mirror usage and to understand their decision-making processes. Combined the Theory of Planned Behavior (TPB) and Task Technology Fit (TTF), and introduced the extended variable of perceived danger, this study explores the psychological factors that shape e-bike users' willingness and behavior regarding rearview mirror usage from a social psychology perspective.
Methods: A questionnaire survey was conducted on e-bike users (N = 704) in China. The data collected included demographic characteristics, components integrated the TPB and TTF, and relevant extended variables. Structural equation analysis (SEM) was used to analyze the data, as well as demographic variable analysis.
Results: The integration of the TPB and TTF models provides an effective framework for explaining and predicting the behavior and intentions of Chinese e-bike users regarding rearview mirror usage. The results of the model show that rearview mirrors fit e-bikes riding task, attitudes toward rearview mirror usage, and e-bike users characteristics associated with rearview mirror use increase e-bike users' willingness to use rearview mirrors. The extended TPB construct of perceived risk did not emerge as a formidable predictor in the e-bike riders' adoption of rearview mirrors. Additionally, results from multiple-group SEM analysis of four demographic variables (age, gender, e-bike riding experience, rearview mirror usage experience) suggest significant differences among e-bike users in using rearview mirrors while riding on the road.
Conclusions: This study establishes the validity of the integrated model of TPB and TTF model in predicting the use of rearview mirrors by e-bike users. Furthermore, the current findings may provide theoretical support for developing intervention strategies to promote rearview mirror usage, safety education initiatives, and the design improvements of rearview mirrors for e-bikes users.
期刊介绍：
The purpose of Traffic Injury Prevention is to bridge the disciplines of medicine, engineering, public health and traffic safety in order to foster the science of traffic injury prevention. The archival journal focuses on research, interventions and evaluations within the areas of traffic safety, crash causation, injury prevention and treatment.
General topics within the journal''s scope are driver behavior, road infrastructure, emerging crash avoidance technologies, crash and injury epidemiology, alcohol and drugs, impact injury biomechanics, vehicle crashworthiness, occupant restraints, pedestrian safety, evaluation of interventions, economic consequences and emergency and clinical care with specific application to traffic injury prevention. The journal includes full length papers, review articles, case studies, brief technical notes and commentaries.
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