Influencer Marketing on TikTok: Role of Content and Reviewer-Related Signals

Abstract

This work investigates the determinants of influencer marketing within the TikTok platform context that enhance followers’ positive behavioral responses toward influencers. Drawing upon the signaling theory, our study examines how content-related signals (i.e. perceived review quality, review consistency, and paid communication) and influencer-related signals (i.e. self-influencer homophily and product-influencer congruence) influence followers’ perceived information diagnosticity and influencer credibility, which consequently affect followers’ intention to follow and recommend influencers. Accordingly, this study adopts a context-specific but theory-driven approach, examining influencer marketing on TikTok through followers’ responses to content generated by a focal influencer. Surveys were conducted among 289 followers of a well-known beauty TikTok influencer, and structural equation modeling was used to test the relationships among variables. The results showed that perceived review quality and review consistency significantly explain information diagnosticity, whereas paid communication did not. Besides, self-influencer homophily and product-influencer congruence were found to significantly increase reviewer credibility, ultimately contributing to followers’ intention to follow and recommend the influencer. This work is the first attempt to examine the simultaneous effects of both influencer characteristics and content attributes on the behavioral intentions of TikTok followers. This study also extends the generalizability of the signaling theory and enriches the influencer marketing literature to the new context of TikTok.