Cognitive Determinants and Technological Adoption: Exam-ining Behavioral Intention Mechanisms in Artisanal Design Practices Mediated by AI-Generated Content

Artificial Intelligence-Generated Content (AIGC) is a rapidly evolving technology with significant computational and creative potential, offering new possibilities in design, aesthetics, and process innovation. However, traditional artisans view AIGC as a potential threat to the authenticity and value of their work. Research on artisans' acceptance of AIGC is limited. This study aims to identify the key factors influencing artisans’ willingness to adopt AIGC-assisted design and develop a validated measurement scale and evaluation model. A mixed-methods approach combining qualitative and quantitative research was used, including user interviews and literature review. Exploratory factor analysis and multiple regression analysis identified six key factors affecting adoption: serendipity for design, artisanal epistemology, productivity enhancement, and technical usability. Simulated craft authenticity and epistemic openness did not show direct effects. The study highlights the need for technology integration that respects artisans' cognitive frameworks and creative traditions, advocating for a shift from technological neutrality to cultural adaptation and collaborative co-creation.