Research on Cultural IP Digital Design Generation and User Acceptance Based on CNN and AIGC

This study aims to investigate the impact of digital design generation for cultural IPs based on Convolutional Neural Networks (CNN) and AI-generated content (AIGC) on user acceptance, whilst analyzing the moderating role of design management capabilities within this process. Dunhuang patterns were selected as cultural IP material, with design proposals generated through CNN feature extraction combined with the Stable Diffusion model. Hypothesis testing employed Structural Equation Modelling (SEM). Findings indicate that design management capabilities play a pivotal integrative role in the process of enabling cultural IP design generation through CNN and AIGC technologies. Establishing a human-machine co-creation design management pathway-guided by strategic positioning, underpinned by resource integration, and safeguarded by innovation management-constitutes the core approach to achieving the unification of technological and cultural value.