BRAND AUTHENTICITY IN DIGITAL MARKETS: EFFECTS ON CONSUMER TRUST AND BRAND LOYALTY

Abstract

Digital markets have intensified a paradox at the heart of brand management: consumers demand authenticity from commercial actors while platforms reward polished, algorithmically optimized performance. Despite a robust literature on brand authenticity in offline contexts, the construct’s dimensionality, antecedents, and downstream consequences remain poorly specified for digital environments marked by generative content, parasocial influencer dynamics, and platform-mediated visibility. This study addresses that gap through an explanatory sequential mixed-methods design. In Phase 1, 28 in-depth interviews with consumers across four digital platforms (Instagram, TikTok, X, and brand-owned applications) were subjected to reflexive thematic analysis, yielding a four-dimensional construct of digital brand authenticity: transparency of intent, narrative consistency, provenance of voice, and refusal of optimization. In Phase 2, a survey of 648 active digital consumers was analyzed via confirmatory factor analysis and structural equation modeling. The hypothesized model fit the data well (χ²/df = 2.31; CFI = 0.96; RMSEA = 0.045; SRMR = 0.041) and supported a fully mediated pathway from perceived authenticity to brand loyalty through cognitive and affective trust. A multi-group analysis revealed that platform architecture (algorithmically curated versus relationally curated) significantly moderated the authenticity→trust pathway (Δχ² = 14.7, p < .001). The study advances signaling theory for algorithmic markets, introduces the authenticity debt concept, and offers managerial guidance on platform-contingent authenticity strategies.

Keywords: Brand authenticity; digital marketing; consumer trust; brand loyalty; signaling theory; multi-group SEM