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The Influence of TikTok's Affiliate Marketing Program on Consumer Purchase Decisions Adam Hernawan; Mamduh Rihadatul Aisy
Jurnal Ekonomi Teknologi dan Bisnis (JETBIS) Vol. 5 No. 3 (2026): Jurnal Ekonomi, Teknologi dan Bisnis
Publisher : Al-Makki Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57185/zt6qjg70

Abstract

The rapid proliferation of social commerce platforms has fundamentally transformed consumer purchasing behavior, with TikTok emerging as a dominant channel for affiliate marketing in Southeast Asia. Despite the platform’s growing commercial significance, empirical understanding of how its affiliate programs influence Indonesian consumer purchase decisions remains limited. This study aims to analyze the influence of affiliate marketing programs conducted by influencers on TikTok on consumer purchase decisions in Indonesia, and to evaluate key factors determining program effectiveness, including content format, influencer engagement, and audience interaction mechanisms. A qualitative approach with an exploratory descriptive design was employed. Data were collected through in-depth semi-structured interviews with TikTok platform management representatives and licensed affiliate employees (n=30), supplemented by systematic participatory observation of 50 TikTok videos featuring affiliate marketing content. Thematic analysis was applied to identify recurring patterns across data sources. Influencers with authentic and emotionally resonant audience relationships demonstrated substantially higher conversion rates. Engagement-driven content elements, including call-to-action prompts and promo codes embedded in concise video formats (15–30 seconds), were identified as primary drivers of purchase decisions. The findings offer practical guidance for marketers in optimizing affiliate campaign design on TikTok and advance the theoretical understanding of social commerce dynamics and influencer-mediated consumer behavior in emerging digital economies. Future research should employ mixed-methods or quantitative designs with broader samples to validate and extend these findings.