PurposeIn spite of the increasing organic and interactive marketing activities over social media, a general understanding of the source credibility of voluntary user-generated content (UGC) is still limited. In line with the social identity theory, this paper examines the effects of consumers' perceived source credibility of UGC in YouTube videos on their attitudes and behavioral intentions. Additionally, source homophily theory is included to predict the antecedent of source credibility.Design/methodology/approachThree hundred and seventy two Generation Y respondents were interviewed using snowball sampling. Data were analyzed with component-based structural equation modeling technique of partial least squares-structural equation modeling (PLS-SEM).FindingsFindings confirmed that perceived source credibility indirectly affects purchase intention (PI) and electronic word-of-mouth via attitude toward UGC. Besides, perceived source credibility mediates the effect of perceived source homophily on attitude toward UGC.Practical implicationsSince today's consumers have begun to trust and rely more on UGC than company-generated content on social media when making purchase decisions, companies may reconsider democratizing certain aspects of their branding strategies. Firms may fine-tune their marketing communication budgets – not only just by sponsoring public figures and celebrities but also by nurturing coproductive engagements with independent content creators who are ordinary consumers. Endowed with their imposing credibility, these micro-influencers and prosumers have high potentials to be uplifted to brand ambassadors.Originality/valueWhile consumers' purchase outcome can be measured easily using metrics and analytics, the roles of source homophily in stages leading up to the purchase is still elusive. Drawing on the rich theoretical basis of source homophily may help researchers to understand not only how credibility and attitude are related to PI but also how this nexus generates positive word of mouth among UGC followers within the social media circles.
Structural equation modeling–based effect-size indices were used to evaluate and interpret the impact of response shift effects
