Abstract
Visual generative artificial intelligence (visual GenAI) is increasingly used to communicate urban regeneration proposals, but how public evaluations relate to scheme support remains insufficiently understood. Using the Fengtian Factory in Shenyang, China, this study examined three AI-visualized industrial heritage regeneration schemes across three scenes within the Stimulus–Organism–Response framework. A total of 360 participants evaluated all nine stimuli in a fixed sequence, yielding 3240 evaluation records. Multilevel confirmatory factor analysis, multilevel structural equation modeling, participant-level cluster bootstrap, and repeated-measures analysis of variance were used. Perceived cultural authenticity and perceived realism were positively associated with perceived trust in visual representation; trust, cultural authenticity, and affective comfort were positively associated with scheme support. The exhibition-oriented scheme received the highest cultural authenticity and trust ratings, whereas the shaded relaxation-oriented scheme received the highest affective comfort ratings. Despite these differences in perceived cultural authenticity and affective comfort, overall scheme support did not differ significantly across the three schemes. Perceived realism also showed no significant between-scheme differences. Scheme contrasts showed oppositely directed indirect associations with support through cultural authenticity and trust and through affective comfort. These findings distinguish evaluations that differentiate among schemes from evaluations associated with trust and support, informing the assessment of AI-visualized industrial heritage regeneration.