Table 1

Summary of prior literature and research gap

Literature streamTheoretical focusPotential limitationsPresent study
Parasocial researchPrior work distinguishes parasocial interaction as a situational response during bonding with a specific media figure (Auter and Palmgreen, 2000; Möri et al., 2026; Schramm and Hartmann, 2008; Stever, 2017; Tukachinsky et al., 2020)The literature is clearer on process and relationship states than on a stable predisposition that exists before a target-specific bond forms. As a result, less is known about how predisposition or trait-based parasocial tendency shapes early-stage evaluations before a target-specific relationship has developedRather than examining established parasocial relationship, the present study focuses on whether predisposition or trait-based parasocial tendency predicts early-stage evaluations of unfamiliar influencers
Influencer marketingStudies on influencers show that parasocial interaction or parasocial relationship can strengthen trust, credibility and purchase intention toward a focal influencer (Chung and Cho, 2017; Lim and Lee, 2023; Reinikainen et al., 2020; Sokolova and Kefi, 2020)These studies are largely target-specific and post-exposure. They provide less insight into how consumers respond when the influencer is unfamiliar and a parasocial bond has not yet formedThe present study examines whether parasocial tendency shapes early-stage endorsement trust and purchase intention even when consumers encounter unfamiliar influencers
Virtual influencer researchPrior work compares human and virtual influencers and shows that social response depend on human-likeliness, similarity, authenticity and related cues (Allal-Chérif et al., 2024; Lee et al., 2025; Liu and Lee, 2024; Lou et al., 2022; Qu and Baek, 2023; Rejón‐Guardia et al., 2026; Stein et al., 2022)This stream is strong on stimulus cues but weaker on audience predispositions. It explains which cues matter, but less clearly for whom such cues activate trustThe present study introduces parasocial tendency as the audience-side predisposition that may be differently activated across human versus virtual influencer contexts
Trust research in AI mediated contextsResearch shows that anthropomorphism, social presence, realism and authenticity shape reactions to CGI influencers, virtual agents and AI endorsers (Ahn et al., 2022; Dabiran et al., 2024; Mouritzen et al., 2023; Sands et al., 2022)These variables are typically modelled as direct predictors or mediators, but not as boundary conditions that determine when a pre-existing parasocial tendency becomes consequentialFollowing TAT, the present study treats anthropomorphism as a higher-order boundary condition that shapes whether parasocial tendency is activated and therefore translated into endorsement trust
Trust in artificial agents and recommendation contextsPrior work shows that trust in artificial agents can arise from competence, credibility and informational reliability even in the absence of a mature interpersonal bond (Kim and Wang, 2024; Sharp and Sebrechts, 2020)Influencer research often leaves unclear whether the relevant trust mechanism is interpersonal, relational trust or source-based endorsement trust. This ambiguity is especially problematic for virtual influencersThe present study clarifies that the focal mediating pathway is endorsement trust, allowing consumers to trust a recommendation without assuming reciprocal care from the influencer
Source(s): Authors’ own work

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