Blurring the line: A more complete conceptualization of influencer-generated content and its implications for deception

Deception within influencer-generated content (IGC) remains a critical issue, yet existing literature has largely examined sponsored and non-sponsored content in isolation. Drawing on Social Exchange Theory, this study conceptualizes IGC as a multidimensional form of marketing communication, comprising non-sponsored content (user-generated content and advocacy content) and sponsored content (disclosed and non-disclosed), and examines how these content types and their interactions with influencer tiers (micro, macro, and mega) are associated with low-level (views, likes, and shares) and high-level (comments and bookmarks) engagement. Our empirical analysis of Xiaohongshu data identifies a transparency premium. Within the macro-influencer benchmark, disclosed sponsored content is associated with the strongest engagement across all five outcomes, and the interaction estimates indicate that this disclosed-content advantage is especially strong for mega influencers on views, likes, comments, and bookmarks. By contrast, non-disclosed sponsored content is associated with lower engagement across all five outcomes; this penalty is attenuated for micro influencers on selected outcomes, particularly shares and comments, but amplified for mega influencers across all five outcomes. By offering a more complete conceptualization of IGC and clarifying how content type and influencer tier jointly shape engagement, this study offers implications for disclosure design, influencer-content alignment, and regulatory policy.