How generative AI shapes designers' cultural heritage revitalization intention: process and content cues in AI-assisted cultural heritage design.

As generative AI becomes increasingly involved in cultural heritage design, designers' evaluations of AI collaboration are shaping cultural revitalization practices. Yet existing research offers limited explanation of how AI characteristics affect designers' willingness to engage in cultural heritage revitalization or how professional experience conditions this process. Based on the stimulus-organism-response (S-O-R) framework, this study develops a dual-path moderated mediation model. It examines how AI process cues and AI-generated content cues influence revitalization intention through psychological ownership and perceived output quality. Using data from 312 Chinese designers with experience in generative AI-assisted cultural heritage design, the study combines PLS-SEM, multi-group analysis, fsQCA, and LDA text analysis. The results show that algorithmic autonomy reduces psychological ownership, whereas interaction transparency and interaction depth enhance it. Cultural authenticity improves perceived output quality, while the effect of visual complexity varies by experience level. Experienced designers rely more on psychological ownership, whereas early-career designers rely more on perceived output quality. fsQCA and LDA further reveal multiple configurations of high revitalization intention and two evaluative orientations in design discourse: ownership-oriented and quality-oriented. This study clarifies the dual-evaluation mechanism of AI-assisted cultural heritage design and offers behavioral evidence for generative AI's role in cultural translation and sustainable dissemination.