Sustainable Use Intention of Text-to-Image Generative AI in Higher Education: An S–O–R Model with Parallel Trust and Risk Pathways

In light of the rapid adoption of text-to-image (T2I) tools in higher education, this study develops a stimulus–organism–response (S-O-R) model to explain the sustainable and responsible use intentions of text-to-image generative AI tools in higher education. Focusing on both university students and faculty, the model conceptualizes perceptions of ease of use, information quality, and ethical awareness as external stimuli; technology- and ethics-related anxiety as internal emotional states; and algorithmic trust, perceived risk, and sustainable use intention as behavioral evaluations and responses. Grounded in the Stimulus–Organism–Response (S–O–R) framework, we integrate the Technology Acceptance Model (TAM), Technology Threat Avoidance Theory (TTAT), and the DeLone–McLean (D&M) model to propose a layered mechanism, with personal innovativeness serving as a moderator. Utilizing 807 valid survey responses, we employed structural equation modeling and fuzzy-set qualitative comparative analysis. The results reveal that (1) the overall chain is supported: perceived ease of use, information quality, and ethical awareness primarily influence sustainable use intention indirectly through anxiety, trust, and risk; (2) although higher usability and quality do not alleviate anxiety, they coexist within a complex pattern of trust amid anxiety; and (3) high levels of personal innovativeness diminish the linear effects of trust and risk on intention. Configurational evidence further indicates multiple pathways leading to high sustainable intention, whereas low intention is typically characterized by uniformly low perceptions, emotions, evaluations, and innovativeness. By framing sustainable adoption through a coupled trust–risk–anxiety lens, this study extends the understanding of generative AI use in education and offers actionable implications for promoting responsible and sustainable practices in universities.