Toward a theory of consumer digital trust: Meta-analytic evidence of its role in the effectiveness of user-generated content

Rachel E. Hochstein (), Colleen M. Harmeling () and Taylor Perko ()
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Rachel E. Hochstein: University of Missouri – Kansas City
Colleen M. Harmeling: Florida State University
Taylor Perko: Florida State University

Journal of the Academy of Marketing Science, 2025, vol. 53, issue 4, No 6, 1034-1054

Abstract: Abstract Consumers seek out online user-generated content to inform their purchase decisions because they perceive content created by other consumers as more believable than marketing communications. This research provides a theory of consumer digital trust in which consumer trust in user-generated content requires a digital environment that minimizes consumer suspicion of misrepresented or missing content. The theory is supported with empirical evidence from a hierarchical meta-analysis of 128 effects from 19 online platforms over 19 years (2004–2022). Account verification features, which alleviate suspicions of misrepresented content creator identities, increase the effect of user-generated content on firm performance, but content-enhancing features, such as photo filters, that can prompt suspicion of misrepresented brand experiences, weaken this link. Content-removal features that can spark speculation of missing information in content creators’ historical content and platform moderation media, which creates questions about missing content in brand conversations, weaken the influence of some user-generated content.

Keywords: User-generated content; Online engagement behaviors; Meta-analysis; Customer reviews; Social media; Online trust; Content moderation; Electronic word of mouth (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11747-023-00982-y

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