ThaiGAM: A dual-moderation framework for GenAI adoption in open learning innovation

The study investigates the adoption of Generative AI (GenAI) as a complex socio-technical phenomenon within Thailand's emerging open learning innovation ecosystem. By synthesizing the Theory of Planned Behavior (TPB) and Technology Acceptance Model 2 (TAM2) and extending them with constructs of trust and privacy, this integrated framework moves beyond linear adoption models to capture the system's complexity. Analysis of data from 1061 university students reveals that innovation diffusion in this ecosystem is driven primarily by social dynamics (Social Norm) and institutional-level trust (Trust in AI), rather than individual calculations of utility. This finding challenges traditional adoption assumptions, highlighting the power of collective behavior in a collectivist culture. Furthermore, the study identifies an emergent property of "critical trust," where heightened trust fosters greater privacy awareness, adding another layer of complexity to the user-technology relationship. With gender and academic level acting as significant moderators, the research reveals important implications for implementation. Successful GenAI integration depends less on the technology itself and more on managing the social architecture and fostering trust across educational institutions.