Modeling behavioral intentions to adopt autonomous vehicles: A dual SEM–FsQCA approach to trust, technology acceptance, and the moderating role of social influence

Abstract

Autonomous vehicles have the potential to transform transportation by increasing efficiency, safety, and sustainability. However, their acceptance remains low, particularly in emerging markets like Armenia, where issues of public trust and perception pose significant barriers. This study aims to examine behavioral intents to embrace autonomous vehicles by extending the Technology Acceptance Model with trust, social influence, and user attitudes. The study employs a dual analytical method, including structural equation modeling and fuzzy-set qualitative comparative analysis, to find both linear and configurational pathways that influence adoption intentions. The results of structural equation modeling show that trust highly affects behavioral intention, both directly and indirectly through perceived usefulness and attitudes. In addition, social influence moderates the relationships, particularly those between perceived ease of use and attitude, as well as trust and intention. The results of fuzzy-set Qualitative Comparative Analysis reveal multiple sufficient combinations of factors leading to high behavioral intention. Attitude emerged as a central factor in most configurations that indicated a strong intention to adopt. This study increases our understanding of how social and cognitive factors influence the adoption of autonomous vehicles. It highlights the importance of building trust and improving the usability of the design to generate positive perceptions and a desire to utilize it. The findings suggest recommendations for regulators, autonomous vehicle manufacturers, and marketers looking to promote the use of self-driving cars in emerging nations.