The successful implementation of autonomous delivery vehicles (ADVs) hinges on user acceptance. To address existing theoretical ambiguities, this study develops and validates a comprehensive model integrating the technology acceptance model (TAM), diffusion of innovation (DOI) theory, and Kirton’s adaption–innovation theory. Data were collected from 388 experienced early adopters in China via an online survey, and the model was analyzed using partial least squares structural equation modeling (PLS‐SEM). The results confirm that relative advantage and compatibility positively influence attitude (ATT), which in turn predicts usage intention. However, by using a collected cross‐sectional sample, both perceived risk and complexity were found to have a significant positive influence on ATT in this specific context. Furthermore, Kirton’s cognitive styles exerted a direct positive effect on usage intention rather than a moderating one. A multigroup analysis revealed distinct acceptance pathways: men’s ATTs were driven by utilitarian factors (e.g., compatibility) while women’s were driven by experiential factors (risk and complexity), with women also demonstrating a stronger intention to recommend the service. This study contributes to the literature by challenging the conventionally negative roles of risk and complexity for experienced users and proposing a new integrated framework. The findings offer practical insights for developing phase‐based and gender‐differentiated marketing strategies and inform human–computer interface design for ADVs.
Zhuoxi Yu (Thu,) studied this question.
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