Exploring fashion designers’ acceptance of AIGC: A dual-pathway analysis from the stimulus–organism–response perspective

Abstract

Artificial Intelligence Generated Content (AIGC) is increasingly used in creative design. Understanding fashion designers’ willingness to adopt these tools has therefore become important for both research and practice. Drawing on the Stimulus–Organism–Response (SOR) model, this study integrates Self-Determination Theory (SDT) with perceived risk, social influence, and facilitating conditions. It examines how these contextual stimuli shape designers’ basic psychological need satisfaction and behavioral intention. We analyzed 318 valid responses with complete data for all 21 measurement items from Chinese fashion-design practitioners using partial least squares structural equation modeling (PLS-SEM). Perceived risk negatively predicted autonomy, competence, and relatedness, whereas social influence and facilitating conditions positively predicted these organismic states. Autonomy, competence, and relatedness each positively predicted behavioral intention, with competence showing the largest coefficient (β = 0.520, p < 0.001). Bootstrapped analyses confirmed all nine specific indirect effects from the three stimuli to behavioral intention through the three psychological needs. These findings clarify how SOR and SDT jointly explain technology adoption among fashion designers. They also provide practical guidance for copyright governance, prompt training, and collaboration between designers and AI.