{"title":"Exploring antecedents of passengers’ behavioral intentions toward autonomous buses: A decomposed planning behavior approach","authors":"Kai-Chieh Hu , Li-Hao Yang","doi":"10.1016/j.jpubtr.2025.100116","DOIUrl":null,"url":null,"abstract":"<div><div>The increasing prominence of autonomous buses in metropolitan transportation has sparked considerable interest. However, the absence of a comprehensive theoretical framework hinders the systematic exploration of factors influencing passengers’ behavioral intentions regarding autonomous buses. This study addresses this gap by employing the decomposed planning behavior theory to investigate the antecedents of passengers’ behavioral intentions. Additionally, the study examines the impact of travel anxiety and perceived risk on passengers’ attitudes. Data were collected through a questionnaire survey, and structural equation modeling was utilized to rigorously test the research model. The findings reveal that purchase intention is positively influenced by novelty seeking, subjective norm, and perceived behavioral control, while being negatively impacted by travel anxiety. Conversely, travel anxiety is negatively influenced by novelty seeking but positively affected by perceived risk. Moreover, interpersonal influence positively affects subjective norm, and self-efficacy has a positive influence on perceived behavioral control. This study offers valuable insights for current and potential bus operators and government entities seeking to advance the promotion of autonomous buses in metropolitan areas.</div></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"27 ","pages":"Article 100116"},"PeriodicalIF":2.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Public Transportation","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1077291X25000013","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
The increasing prominence of autonomous buses in metropolitan transportation has sparked considerable interest. However, the absence of a comprehensive theoretical framework hinders the systematic exploration of factors influencing passengers’ behavioral intentions regarding autonomous buses. This study addresses this gap by employing the decomposed planning behavior theory to investigate the antecedents of passengers’ behavioral intentions. Additionally, the study examines the impact of travel anxiety and perceived risk on passengers’ attitudes. Data were collected through a questionnaire survey, and structural equation modeling was utilized to rigorously test the research model. The findings reveal that purchase intention is positively influenced by novelty seeking, subjective norm, and perceived behavioral control, while being negatively impacted by travel anxiety. Conversely, travel anxiety is negatively influenced by novelty seeking but positively affected by perceived risk. Moreover, interpersonal influence positively affects subjective norm, and self-efficacy has a positive influence on perceived behavioral control. This study offers valuable insights for current and potential bus operators and government entities seeking to advance the promotion of autonomous buses in metropolitan areas.
期刊介绍:
The Journal of Public Transportation, affiliated with the Center for Urban Transportation Research, is an international peer-reviewed open access journal focused on various forms of public transportation. It publishes original research from diverse academic disciplines, including engineering, economics, planning, and policy, emphasizing innovative solutions to transportation challenges. Content covers mobility services available to the general public, such as line-based services and shared fleets, offering insights beneficial to passengers, agencies, service providers, and communities.