Influencer Marketing in Web 3.0: How Algorithm-Related Influencer following Norms Affect Influencer Endorsement Effectiveness

Abstract

Guided by previous literature on social norms and influencer marketing, we explored the relationship between algorithm-related influencer following norms and influencer marketing effectiveness. To fulfill the research goal, we surveyed 475 qualified Instagram influencer followers who use Instagram, follow at least one influencer on Instagram currently, and have encountered the influencer’s product recommendations. Using PLS-based structural equation modeling, we found that people’s influencer following norms played a significant role in shaping influencer endorsement effectiveness (e.g. influencer following gratifications, perceived influencer characteristics, and effectiveness of influencer product recommendation). Moreover, people’s exposure to the algorithmic social media environment (i.e. suggested and top posts provided by Instagram’s recommendation algorithms) is related to their perceived influencer following norms. We provide implications and future research directions.