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Cited by 369

The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.

Influencer marketing on TikTok: The effectiveness of humor and followers’ hedonic experience

Open access
Barta, Sergio, Belanche, Daniel, Fernández, Ana, Flavián, Marta·2023·Journal of Retailing and Consumer Services
DOI 10.1016/j.jretconser.2022.103149
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Abstract

This work examines the determinants of the success of influencer marketing on the youth-focused TikTok, the fastest growing social network. It analyses the effects of influencers' account characteristics (originality, quality, quantity and humor) on their followers' hedonic experience and perceived opinion leadership, and how these impact on their intentions to follow influencers’ accounts and advice. A survey of followers of a popular Spanish TikTok influencer showed that originality and opinion leadership play important roles and that, because TikTok is distinctive, humor increased the effectiveness of messages (through hedonic experience). Suggestions are made to advance the understanding of this novel phenomenon.

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Crossref · 10.1016/j.jretconser.2022.103149

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Metadata

Authors
Barta, S., Belanche, D., Fernández, A., & Flavián, M.
Venue
Journal of Retailing and Consumer Services
Publisher
Elsevier BV
Published
2023-01
Volume
70
Pages
103149
ISSN
0969-6989 (ISSN-L)
DOI
10.1016/j.jretconser.2022.103149
OpenAlex
W4297991825
Cited by
369
References
85
FWCI
103.95
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Influencer marketing on TikTok: The effectiveness of humor and followers’ hedonic experience. https://app.cochat.ai/papers/10.1016/j.jretconser.2022.103149
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Barta, S., Belanche, D., Fernández, A., & Flavián, M. (2023). Influencer marketing on TikTok: The effectiveness of humor and followers’ hedonic experience. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2022.103149

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.