Pet Influencer in Influencer Marketing: Examining How Pet Influencer Attributes Could Influence Audience Purchase Intention - Syeikhah Ananda Nurrahma; Safina Alya Zahira; Hasanah Dinar Ayati; Evelyn Hendriana (Journal of Economics and Management, 2026)
The development of digital marketing has introduced social media influencers (SMIs) as key players in shaping consumer perceptions and behaviors. Although human influencers remain more familiar, pet influencers, a specific type of SMI, also hold strong potential to influence customer responses. However, research on pet influencers remains limited. Although the elaboration likelihood model (ELM) has been widely applied to explain persuasion in human influencer marketing, its applicability to non-human influencers remains largely unexplored. Using ELM, this study examines the effectiveness of pet influencers in shaping audiences' purchase intention and perceived sincerity through three proposed attributes: authenticity, attractiveness, and anthropomorphism. Data were collected from 157 audiences who had viewed pet influencer content at least three times within the past year and analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that anthropomorphism is the only attribute related to both purchase intention and perceived sincerity. Authenticity is directly related to perceived sincerity but not purchase intention, while attractiveness shows no relation to either outcome. Perceived sincerity itself does not translate into purchase intention. These results suggest that persuasion in the pet influencer context is driven more by the ELM peripheral route, centered on emotional and symbolic cues such as anthropomorphism, than by the central route typically associated with authenticity in human influencer marketing. As most measurement items were adapted from human influencer research, they may not fully capture pet influencer traits, and future studies are encouraged to develop and validate measures specific to the pet influencer context.