Tourists’ Vlog sharing motivations and perceived advertising value to predict e-referral behavior: A PLS-SEM and NCA approach
This study aims to understand the impact of tourists’ referral-sharing motivations (e.g., altruism, trust, reputation, expected benefits, and expected relationships) on the advertising value of video blogging (Vlogs), to predict e-referral behavior on social media. Using the Social Exchange Theory (SET), we collected 280 valid cases, and the data were analyzed using the partial least squares–structural equation modeling (PLS-SEM) approach. Our findings show a positive relationship between referral-sharing motivations (e.g., altruism, reputation, and expected relationships) and Vlog advertising value, subsequently influencing tourists’ e-referral behavior. However, tourist referral-sharing motivations (e.g., expected benefits and trust) fail to influence perceived Vlog advertising value. Our findings suggest that content creators and marketers must prioritize the production of Vlogs that possess not only entertainment value but also credibility, while simultaneously minimizing any elements that have the potential to provoke viewer irritation. We have expanded SET to digital contexts, focusing on social motivations in sharing. This study contributes to understanding how user-generated content marketing and the SET work together by creating and assessing a framework that explains why tourists share travel Vlogs on social media.
Authors
- Amir Zaib Abbasi (ORCID: https://orcid.org/0000-0001-8220-1989)
- Mehedi Hasan (ORCID: https://orcid.org/0000-0003-3294-7402)
- Ding Hooi Ting (ORCID: https://orcid.org/0000-0002-5957-8056)
- Farhan Mirza (ORCID: https://orcid.org/0000-0001-9472-8905)
Institutions
- King Fahd University of Petroleum and Minerals (SA)
- Universiti Teknologi Petronas (MY)
- Victoria University of Wellington (NZ)
Publication Details
- Journal
- Tourism and Hospitality Research
- Published
- 2025-10-03
- DOI
- https://doi.org/10.1177/14673584251382492
- Primary Topic
- Digital Marketing and Social Media
- Type
- article
- Field-Weighted Citation Impact
- 0.00