AI-GENERATED AND USER-GENERATED CONTENT AND PURCHASE INTENTION THROUGH PERCEIVED AUTHENTICITY ON TIKTOK

This study examines the relationships of AI-generated content (AIGC) and user-generated content (UGC) with purchase intention and the mediating role of perceived authenticity among TikTok users in Lhokseumawe, Indonesia. A quantitative survey employed purposive sampling and an online questionnaire. Of 133 responses received, 126 met the eligibility criteria. Data were analyzed using partial least squares structural equation modeling with SmartPLS 4. AIGC was positively associated with perceived authenticity (β = 0.270, p = .001), but its direct relationship with purchase intention was not significant (β = −0.075, p = .545). UGC was positively associated with perceived authenticity (β = 0.486, p < .001) and purchase intention (β = 0.302, p = .023). Perceived authenticity was also positively associated with purchase intention (β = 0.397, p < .001). Significant indirect relationships were identified for AIGC (β = 0.107, p = .009) and UGC (β = 0.193, p = .002). The model explained 47.1% of the variance in perceived authenticity and 34.9% in purchase intention. These findings support attention to authenticity in digital content strategies, while the local, observational survey limits causal interpretation and generalization.