Cross-National Evidence on Influencer-Driven Green Choice: A Moderated-Mediation model of Authenticity, Parasocial Ties, and Greenwashing Exposure

Balaskas, S and Yfantidou, I ORCID: 0000-0003-3200-2185 Cross-National Evidence on Influencer-Driven Green Choice: A Moderated-Mediation model of Authenticity, Parasocial Ties, and Greenwashing Exposure. Frontiers in Communication. ISSN 2297-900X (Accepted)

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Abstract

Social media influencers are essential to sustainability communication, but the mechanisms through which their messages convert into environmentally conscious consumer behavior remain under-specified. This research examines two antecedents—perceived influencer authenticity (AUTH) and parasocial relationship (PSR)—within a conditional-process framework that identifies green trust (TRUST) as the proximal mechanism. The design additionally involves two skepticism constructs: perceived greenwashing risk (PGR) at the post level and prior greenwashing exposure (PGE) at the individual level. Utilizing recall-anchored, cross-national survey data from Greece (n = 376) and the United Kingdom (n = 331), analyzed through variance-based structural equation modeling (SEM), we examine direct, mediated, and moderated-mediation relationships. AUTH and PSR exhibit positive associations with sustainable purchase intention across the country and pooled samples, while TRUST offers additional explication power. The conversion of TRUST into intention is weakened by PGE, which functions as a late-stage boundary condition. Conditional-indirect analyses indicate that PGR affects intention via TRUST in all samples, with effects diminishing as PGE rises; PSR only shows a moderate negative mediated component via TRUST in addition to its positive direct association with intention in the UK. Cross-national comparability is supported by measurement and structural invariance. To maintain the conversion efficiency of trust in green decision-making, the findings suggest prioritizing verifiable, value-congruent authenticity, actively managing both PGR and PGE, and matching influencer content with transparent substantiation practices.

Item Type:	Article
Uncontrolled Keywords:	4410 Sociology; 4701 Communication and media studies; 4704 Linguistics
Subjects:	H Social Sciences > HF Commerce > HF5001 Business H Social Sciences > HT Communities. Classes. Races
Divisions:	Liverpool Business School
Publisher:	Frontiers Media S.A.
Date of acceptance:	30 January 2026
Date of first compliant Open Access:	3 February 2026
Date Deposited:	03 Feb 2026 09:34
Last Modified:	03 Feb 2026 09:34
URI:	https://researchonline.ljmu.ac.uk/id/eprint/28028

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