聚焦于人工智能生成（AIGC）广告情境，探讨两种典型披露策略（技术性披露和关系性披露）如何通过信息真实性与表达真实性影响用户信任，并进一步考察用户个体特质（如AI欣赏）与外部情境因素（如广告诉求）在其中所起的调节作用。通过多项情境实验，构建并验证了一个被调节的双中介路径模型。研究发现，技术性披露主要通过提升信息真实性来建立信任，且此效应在高AI欣赏用户和理性广告诉求情境下尤为显著；关系性披露则主要依赖增强表达真实性来促进信任，其影响在低AI欣赏用户和感性广告诉求情境中更为突出。

This study focuses on the context of AI-generated content (AIGC) advertising, aiming to investigate how two typical disclosure strategies—technical disclosure and relational disclosure—influence user trust through the mediating roles of informational authenticity and expressive authenticity, while further examining the moderating effects of AI appreciation and advertising appeals. Through multiple scenario-based experiments, a moderated dual-mediation model was developed and validated. The results showed that technical disclosure primarily built trust by enhancing informational authenticity, with this effect being more pronounced among users with high AI appreciation and in the context of informational advertising appeals. In contrast, relational disclosure fostered trust mainly by strengthening expressive authenticity, proving more effective for users with low AI appreciation and in the context of emotional advertising appeals.