Publication | Open Access
Exploring the Factors Affecting Mode Choice Intention of Autonomous Vehicle Based on an Extended Theory of Planned Behavior—A Case Study in China
205
Citations
71
References
2019
Year
EngineeringBehavioral Decision MakingChoice TheoryAv TechnologyIndividual Decision MakingTravel BehaviorAutonomyDriver BehaviorRisk ManagementManagementAction PlanningConsumer BehaviorTransportation Systems AnalysisDecision TheoryTransportation EngineeringAutomated VehiclesBehavioral SciencesExtended TheoryUser AcceptanceMotivationUser ExperienceInnovative Transport OptionMarketingDecision-makingTechnology Acceptance ModelAutonomous VehicleTechnologyDecision ScienceTransportation Systems
Autonomous vehicle (AV) is an innovative transport option that has the potential to disrupt all industries tied to transportation systems. The advent of AV technology will bring a novel on-demand mobility pattern such as shared autonomous vehicle (SAV). To promote AV technology, it is important to understand which factors influence travelers’ intention to use AVs and SAVs. This paper collected literature from databases such as Scopus, Web of Science and ScienceDirect, and made a systematic review. The study aims to explore the determinants that influence travelers’ behavioral intentions towards use AVs and SAVs based on an extended version of the theory of planned behavior, which incorporates knowledge and perceived risk. This study was tested empirically using a valid survey sample collected from 906 respondents in China. Structural equation model was conducted to investigate the predictors of intentions to use AVs and SAVs. Results showed that knowledge about AV technology and perceived risk are the two main potential obstacles for travelers to use AVs and SAVs. Attitude significantly affects AVs and SAV choice intentions. Subjective norm is the most critical factor affecting the travelers’ intention to use AVs. Perceived behavioral control potentially stymie the travelers’ intention to use SAVs. The findings will enhance the understanding of travelers’ choice motivation from psychological and service perspectives, and provide data support for governments and companies in improving travel management strategies and product services.
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