Dataset on tourists’ perceptions of online user-generated travel content and tourist behavioral responses in Vietnam (2025–2026)

Description

This dataset contains survey data on tourists’ perceptions of online user-generated travel content (UGC) and related behavioral responses toward tourism destinations in Vietnam. The dataset captures tourists’ evaluations of UGC characteristics, including informativeness, authenticity, vividness, and relevance, as well as their engagement with online travel content and subsequent behavioral responses such as revisit intention and destination brand evangelism. Variables related to self-congruity and travel constraints are also included. Data were collected from domestic and international tourists at major tourism destinations across Northern, Central, and Southern Vietnam between December 2025 and February 2026. A structured questionnaire with five-point Likert scale items was administered on-site using a time-location intercept approach with the support of trained research assistants. A total of 1,500 tourists were approached, resulting in 1,347 valid responses after eligibility screening. The repository includes the raw survey dataset, a codebook describing variables and coding schemes, the questionnaire in English and Vietnamese, and the informed consent form used during data collection. The dataset allows replication of statistical analyses using structural equation modeling or other quantitative methods and can support research on digital tourism behavior, online engagement, and destination branding in emerging tourism markets.

Steps to reproduce

1. Download the dataset file “Dataset on tourists’ perceptions of online user-generated travel content in Vietnam (2025–2026).xlsx” from this repository. 2. Open the dataset using statistical software such as SmartPLS 4, SPSS, or R. 3. Refer to the Codebook.xlsx file to identify variable names, coding schemes, and construct definitions. 4. Specify the reflective measurement model including the following constructs: Informativeness (INF), Authenticity (AUT), Vividness (VID), Relevance (REL), UGC Engagement (ENG), Self-congruity (SC), Travel Constraints (TCN), Revisit Intention (RET), and Destination Brand Evangelism (EVA). 5. Evaluate the measurement model using reliability and validity indicators (outer loadings, Cronbach’s alpha, composite reliability, and AVE). 6. Assess discriminant validity using the HTMT criterion. 7. Evaluate the structural model using bootstrapping (5,000 resamples) to obtain path coefficients and significance levels. 8. Examine model explanatory and predictive power using R², effect sizes (f²), and Stone–Geisser Q² values. 9. Run PLSpredict to assess out-of-sample predictive performance.

Institutions

• Foreign Trade University

  Hanoi, Hanoi

Categories

Licence