The antecedents and consequences of perceived warmth and competence in the influencer context: human vs. virtual

In an era where human and virtual influencers coexist, this research integrates the elaboration likelihood model (ELM) and social cognition perspectives to investigate how content and influencer characteristics affect followers' perceptions of an influencer's warmth and competence and subsequently affect their behavior. The 455 valid survey responses (273 = human influencer; 182 = virtual influencer) were empirically examined using structural equation modeling and fsQCA. The results reveal that the central cue (i.e., argument quality) and one peripheral cue (i.e., source credibility) have stronger effects on competence than on warmth, whereas the other two peripheral cues (i.e., visual appeal and physical attractiveness) exert stronger effects on warmth than on competence. Warmth and competence positively affect all types of follower behaviors, with warmth having a stronger effect on hedonic well-being than competence does; however, competence has a stronger effect than warmth does on the other types of behavior. This research contributes to comparative studies on virtual and human influencers by emphasizing content and influencer characteristics as key factors in assessing perceptions of warmth and competence.