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.

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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
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article

Tourists’ Vlog sharing motivations and perceived advertising value to predict e-referral behavior: A PLS-SEM and NCA approach

Amir Zaib Abbasi, Mehedi Hasan, Ding Hooi Ting, Farhan Mirza
Tourism and Hospitality Research
Digital Marketing and Social Media
article

Tourists’ Vlog sharing motivations and perceived advertising value to predict e-referral behavior: A PLS-SEM and NCA approach

Amir Zaib Abbasi, Mehedi Hasan, Ding Hooi Ting, Farhan Mirza
article en

Abstract

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.

Tourism and Hospitality Research
King Fahd University of Petroleum and Minerals (SA), Universiti Teknologi Petronas (MY), Victoria University of Wellington (NZ)
Openalex Percentile: Top 64%
Digital Marketing and Social Media
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Tourists’ Vlog sharing motivations and perceived advertising value to predict e-referral behavior: A PLS-SEM and NCA approach — Amir Zaib Abbasi, Mehedi Hasan, et al. · Tourism and Hospitality Research (2025) | TGRS Research Map | TGRS