Bibliographic record
Abstract
Purpose – This study aims to investigate tourists’ propensity to use travel review websites (TRWs) during the pre- and post-travel stages from a cultural perspective. Design/methodology/approach – This quantitative study is guided by the positivist paradigm. Data were obtained from an online survey, focussing on Australia, Canada, India and Malaysia. Findings – The results indicate significant relationships between country of residence and the time research begins prior to an international or domestic holiday being undertaken; between country of residence and trust levels for information on TRWs; and country of residence and whether or not respondents post reviews on TRWs. These results are discussed using Hofstede’s cultural dimensions. Long-term orientation shows a moderate cultural influence of respondents’ trust of information on TRWs, while a country’s individualistic or collectivist orientation has a strong influence on respondents’ posting/not posting a review on a TRW. Research limitations/implications – Care should be taken when generalising the findings beyond the study population, as no randomisation occurred with survey distribution. Practical implications – The results of this study have implications for managers of tourism businesses wishing to better facilitate information-sharing behaviours of their customers through TRWs. Social implications – The cross-cultural comparisons used in this study add value to tourism studies, particularly when comparing Eastern and Western societies. Originality/value – The study adds to the knowledge base on consumer pre- and post-trip online behaviours, considering the effect of country of residence and any influence from Hofstede’s cultural dimensions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".