Decoding influencer effectiveness: a multiple-inference model of promotional collaboration types on Instagram

Purpose – This study applies the multiple-inference model to investigate how varying forms of influencer promotion (voluntary promotion, government collaboration and brand partnership) trigger distinct motivational attributions that shape consumer attitudes and purchase intentions. Design/methodology/approach – Through a controlled experiment with 277 Instagram users aged 18–45 and robust statistical analysis using ANOVA and hierarchical regression, this study examines how audiences attribute different motives to influencers based on collaboration type. Findings – Results indicate that voluntary promotion predominantly triggers affective motive attribution, which significantly enhances attitudes and purchase intentions. Government collaboration elicits normative motive attribution but shows limited direct effects on persuasion outcomes. Brand partnerships activate calculative motive attribution, which substantially undermines persuasion effectiveness. These findings reveal that perceived authenticity operates through motive attribution rather than merely source characteristics, offering a more sophisticated framework than traditional credibility models. Originality/value – This study provides the first empirical application of the multiple-inference model to Instagram influencer marketing, contributing novel insights into how collaboration type systematically triggers distinct motivational attributions that mediate persuasion outcomes. The research bridges attribution theory with digital persuasion research while offering practical guidance for optimizing influencer collaboration strategies.