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Data · dataset · 2024

Virtual Influencers vs. Human Influencers in the Context of Influencer Marketing: The Moderating Role of Machine Heuristic on Perceived Authenticity of Influencers

Listed in IISH Dataverse and ODISSEI Portal — shown once because both records carry DOI 10.34894/dygqmj

While the popularity of virtual influencers in influencer marketing is on the rise, little is known about the reasons behind their increasing popularity.

Description

Furthermore, there is also a dearth of research examining why and how virtual influencers could be more effective than human influencers in influencing consumer purchase decisions. Drawing on the concept of perceived authenticity of influencers and machine heuristic, this study investigates the effects of influencer type (virtual influencer vs. human influencer) on the perceived authenticity of consumers.

In addition, we also explore if machine heuristic will moderate the perceived authenticity of consumers and whether trust in influencers and purchase intentions will be subsequently associated with the perceived authenticity of the influencer. Results from an online between-subjects designed experiment (N = 130) indicated that virtual influencers were unexpectedly perceived as more authentic than human influencers. Additionally, the perceived authenticity of virtual influencers significantly increased among those with a strong belief in the machine heuristic.

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Subsequently, we found a positive association between the perceived authenticity of influencers and the extent of consumers’ trust in them. Additionally, trust in influencers was positively associated with consumers’ intention to purchase the products they promoted by the influencers. These findings provide valuable insights into the use of virtual influencers for marketing purposes.

Further theoretical and practical implications are discussed.

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Stated by source
Social Sciences · Social Sciences
Provenance · 2 source records, 10 field assertions
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IISH Dataversedoi:10.34894/DYGQMJ10 d agoJSON v1
ODISSEI Portaldoi:10.34894/DYGQMJ6 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].local:field:social-sciencemapping · datasets iisg amsterdamconnector:datasets_iisg_amsterdam@1.0.0/subjects
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