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Overendorsement as a Double-Edged Sword:How Influencer Excess Drives Negative e-WOM, Credibility Loss, and Consumer Avoidance​

Authors: Nila Armelia Windasari; Audi Febiony; Hasna Rizki Mardhiana;

Overendorsement as a Double-Edged Sword:How Influencer Excess Drives Negative e-WOM, Credibility Loss, and Consumer Avoidance​

Abstract

This study investigates the impact of influencers’ Overendorsement on consumer behaviors’ towards the brands and influencers. We also examine the mediating role of negative e-WOM and the moderating role of congruence. Study 1 employed a mixed-method approach to investigate consumer perceptions of Overendorsement via the Critical Incident Technique (CIT), uncovering patterns of excessive language, irrelevant branding, and endorsement frequency. Study 2 tested the relationships between Overendorsement, negative e-WOM, consumer avoidance, congruence, and influencer credibility among 261 respondents. Results confirm that Overendorsement increases negative e-WOM and reduces influencer credibility. Negative e-WOM fully mediates the relationship between Overendorsement and consumer avoidance, while congruence strengthens these effects. The study offers theoretical and practical insights for influencer marketing to balance their endorsement strategies

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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