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This study investigates how four authenticity signals—blockchain traceability, platform self-operation, customer reviews, and compensation commitments—shape consumer purchase intention in the CBEC cosmetics sector. Using experimental data, we tested the mediating role of perceived risk and the moderating effects of traditional signals. The results show that blockchain is the only signal exerting a significant direct effect on purchase intention, while platform self-operation and compensation guarantees influence indirectly influenced by lowering perceived risk, and customer reviews demonstrate limited effectiveness. Mediation analysis confirmed blockchain’s dual signaling role through both direct and indirect pathways, while moderation analysis revealed its strongest impact in low-trust environments lacking institutional or contractual safeguards. Importantly, these findings diverge from prior food-sector studies, suggesting that blockchain’s effectiveness depends on its presentation format and product category. Theoretically, this research refines signaling theory by highlighting the heterogeneity and interdependence of authenticity signals and emphasizing perceived risk as a central mediating mechanism. Practically, the findings suggest that blockchain should anchor authenticity strategies in high-risk contexts while serving as a reinforcing tool when traditional assurances are already strong. The study provides actionable insights for platforms, managers, and policymakers and outlines future research directions, including broader demographic testing, field data, and alternative authenticity signals such as brand reputation and third-party certifications.
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