Access the full text.
Sign up today, get DeepDyve free for 14 days.
Applying social learning theory and the source credibility model, this study aims to investigate the impacts of perceived attractiveness, expertise and trustworthiness of YouTube travel vloggers on viewers’ wishful identification and behavioral intention. The study also aims to examine the effects of vlogger gender on viewers’ perception and on their wish to be like the vlogger.Design/methodology/approachWith an online data collection from 402 YouTube travel vlog viewers, a moderated mediation model was tested using multiple linear regression and multivariate nested linear regression.FindingsThis study found that physical attractiveness, social attractiveness and credibility of travel vloggers positively affected audience wishful identification, among which credibility had the strongest impact. The effect of the travel vlogger’s social attractiveness on viewer wishful identification was even strengthened when the vlogger and the viewer were of different genders. Wishful identification partially mediated the relationship between vloggers’ attributes and viewers’ behavioral intention. Finally, the finding revealed female vloggers were perceived as more physically attractive than males, whereas male vloggers were assessed as more credible than their female counterparts.Originality/valueExpanding upon the literature on mass media and social media, this study explains the mechanism of developing intention to imitate the travel vloggers of YouTube viewers. The findings provide tourism and hospitality managers with solution in choosing the most inspirational travel vlogger to influence consumer behavior.
Journal of Hospitality and Tourism Technology – Emerald Publishing
Published: Aug 5, 2021
Keywords: YouTube; Social media; Social learning theory; Influencer marketing; Travel vlogger; Wishful identification
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.