How Differential Risk Perception Influences Users’ Positive Information Behaviour Toward AIGC Technologies: An Analysis Based on the Cognitive-Affective-Conative (CAC) Model

Recently, the public’s understanding of Artificial Intelligence Generated Content (AIGC) technology remains superficial, which significantly impacts their adoption and use of this technology. This study employs the Cognitive-Affective-Conative (CAC) model to examine the impact of different levels of risk perception on positive information behaviour (PIB) intentions toward AIGC. Through a questionnaire survey (<i>N</i> = 1200), the study finds that the overall risk perception of AIGC among the public significantly and negatively predicts their PIB intentions towards AIGC. And the emotion of AIGC hope plays a notable mediating role, whereas the mediating effect of AIGC anxiety is not apparent. Furthermore, distinct pathways of influence are observed among individuals with different levels of risk perception. The impact of micro-level risk perceptions on AIGC PIB may involve additional mediating pathways beyond AIGC hope. Conversely, within the broader societal and national risk perceptions, the emotion of AIGC hope exerts a more prominent mediating effect.