From Affordance to Actualization: A Study on the Nonlinear Mechanisms of Idea Diffusion in AI-Mediated Online Innovation Communities

In online innovation communities, idea diffusion constitutes a core mechanism through which user-generated ideas are transformed into collective innovation outcomes. However, existing research remains fragmented and lacks a process-oriented explanation of how ideas become actionable and trigger diffusion. This study draws on affordance theory to explain how ideas become actionable and drive diffusion in online innovation communities. Cognitive affordance is operationalized as operability and detail richness, entry affordance as actionability signaling and linguistic hedging, and collaborative affordance as mediating structural position and interaction depth. Using text mining and social network analysis on idea-level data and employing a negative binomial regression model, we find that the effects of affordances are inherently nonlinear. While some affordances exhibit positive linear effects, others follow U-shaped relationships, suggesting threshold-dependent activation mechanisms. The results suggest that AI may influence the activation of affordances and alter certain affordance-diffusion relationships under specific conditions. Theoretically, this study advances affordance theory by introducing an activation-based perspective that captures the nonlinear transformation from perceived possibilities to realized actions. It also integrates content and structural dimensions into a unified framework for understanding idea diffusion. Practically, the findings offer insights for platform governance, particularly in designing content structures, participation mechanisms, and AI-assisted tools that effectively facilitate innovation diffusion.