The impact of the source credibility of Instagram influencers on travel intention: The mediating role of parasocial interaction
Abstract
The primary objective of this study is to determine the impact of the sub-dimensions of source credibility (attractiveness, trustworthiness and expertise), and its secondary objective is to investigate the mediating role of parasocial interaction the effect of the sub-dimensions of source credibility on travel intention. The study was conducted with data obtained from 379 participants and the response rate was found to be 88%. The validity and credibility of the constructs were tested through confirmatory factor analysis, while its hypotheses were tested using path analysis. It was found, as a result of the study, that the trustworthiness and expertise sub-dimensions of source credibility significantly impacted travel intention and played a significant mediating role between the trustworthiness and expertise sub-dimensions of parasocial interaction and travel intention. It is thought that the mediating role of parasocial interaction, which was not previously available in the literature, will make an important contribution to the researchers working on tourism-related marketing research in understanding the travel intention.
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Influencers sharing personal stories create empathy, leading followers to trust their recommendations.
“Influencers sharing personal stories create empathy, leading followers to trust their recommendations (Yılmazdoğan et al. 2021).”
From Influencer Marketing and Tourist Behaviour: A Systematic Literature Review of Attitudes, Intentions and Behaviours in Tourism (2026) · cites this paper as Yılmazdoğan et al. 2021
Cites
The theory of planned behavior
Ajzen, I. (1991) · Organizational Behavior and Human Decision Processes · doi:10.1016/0749-5978(91)90020-t · Cited by 90,587 · see citing works
Mass Communication and Para-Social Interaction
Horton, D., & Richard Wohl, R. (1956) · Psychiatry · doi:10.1080/00332747.1956.11023049 · Cited by 4,380 · see citing works
Ohanian, R. (1990) · Journal of Advertising · doi:10.1080/00913367.1990.10673191 · Cited by 4,043 · see citing works
Goldsmith, R. E., Lafferty, B. A., & Newell, S. J. (2000) · Journal of Advertising · doi:10.1080/00913367.2000.10673616 · Cited by 1,301 · see citing works
Labrecque, L. I. (2014) · Journal of Interactive Marketing · doi:10.1016/j.intmar.2013.12.003 · Cited by 971 · see citing works
Attribution in Social and Parasocial Relationships
PERSE, E. M., & RUBIN, R. B. (1989) · Communication Research · doi:10.1177/009365089016001003 · Cited by 559 · see citing works
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Risk, Trust, and the Roles of Human Versus Virtual Influencers
Ameen, N., Cheah, J.-H., Ali, F., El-Manstrly, D., & Kulyciute, R. (2024) · Journal of Travel Research · doi:10.1177/00472875231190601 · Cited by 133 · see citing works
Past, present, and future scene of influencer marketing in hospitality and tourism management
Polat, E., Çelik, F., Ibrahim, B., & Gursoy, D. (2024) · Journal of Travel & Tourism Marketing · doi:10.1080/10548408.2024.2317741 · Cited by 73 · see citing works
Kılıç, İ., & Gürlek, M. (2024) · Journal of Sustainable Tourism · doi:10.1080/09669582.2023.2273755 · Cited by 71 · see citing works
How does travel social media influencer humour influence viewers’ visit intention?
Li, F. (., & Zhou, Z. (2024) · Current Issues in Tourism · doi:10.1080/13683500.2023.2291114 · Cited by 39 · see citing works
Pourazad, N., Stocchi, L., & Simmonds, L. (2025) · Information Technology & Tourism · doi:10.1007/s40558-025-00330-6 · Cited by 22 · see citing works
Saleh, M. I. (2025) · Journal of Travel Research · doi:10.1177/00472875231214727 · Cited by 15 · see citing works
John, S. P., & Supramaniam, K. (2026) · International Journal of Tourism Research · doi:10.1002/jtr.70226 · Cited by 5 · see citing works
Key social media travel influencer traits impacting followers’ tourist behavior
Kılıçarslan, D., & Caber, M. (2026) · Journal of Hospitality and Tourism Technology · doi:10.1108/jhtt-07-2025-0588 · Cited by 1 · see citing works
Blanco-Moreno, S., González-Fernández, A. M., & Casaló, L. V. (2026) · Journal of Hospitality and Tourism Technology · doi:10.1108/jhtt-02-2025-0168
- Authors
- Yılmazdoğan, O. C., Doğan, R. Ş., & Altıntaş, E.
- Affiliations
- Eskişehir Osmangazi University (TR)
- Manisa Celal Bayar University (TR)
- Corresponding author
- Doğan, Rana Şen
- Venue
- Journal of Vacation Marketing
- Publisher
- SAGE Publications
- Published
- 2021-02-18
- Volume
- 27
- Issue
- 3
- Pages
- 299-313
- ISSN
- 1356-7667 (ISSN-L)
- 1479-1870
- OpenAlex
- W3132754197
- Cited by
- 171
- References
- 6
- Citations by year
- 2026: 42 · 2025: 44 · 2024: 37 · 2023: 28 · 2022: 15 · 2021: 5
- FWCI
- 27.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal Of Vacation Marketing (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Sociology and Political Science › Diverse Aspects of Tourism Research
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Keywords
- source credibility, Instagram influencers, travel intention, parasocial interaction, trustworthiness, expertise, attractiveness, influencer marketing, tourism marketing
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