Modeling behavioral intention to adopt autonomous vehicles: an extended decomposed theory of planned behavior

Abstract

Autonomous vehicles (AVs) have the potential to transform future mobility systems, yet their adoption remains limited in many developing and transitional economies. This study extends the Decomposed Theory of Planned Behavior (DTPB) by incorporating Knowledge of Autonomous Vehicles (KAV) and Perceived Economic Impact (PEI) to explain behavioral intention toward AV adoption. Survey data were collected from 430 licensed drivers in Armenia and analyzed using structural equation modeling and hierarchical regression. The results showed that attitude, subjective norms, and perceived behavioral control significantly predicted behavioral intention, with perceived behavioral control emerging as the strongest determinant. Attitude was positively influenced by perceived usefulness, perceived ease of use, compatibility, and KAV, while subjective norms were shaped by peer and superior influence, and perceived behavioral control by self-efficacy and facilitating conditions. PEI also exerted a significant positive effect on behavioral intention. Moderation analysis indicated that KAV strengthened the relationships between perceived usefulness and attitude and between perceived ease of use and attitude, whereas PEI moderated the effects of subjective norms and perceived behavioral control on behavioral intention. These findings validate the extended DTPB and highlight the importance of cognitive awareness and economic perceptions in promoting AV adoption within transitional economies.

Keywords

Autonomous vehicles / Behavioral intention / Decomposed theory of planned behavior / Knowledge of autonomous vehicles / Economic impact

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