The role of cultural difference and travel motivation in event participation
Bibliographic record
Abstract
Purpose Using a cross-cultural perspective, the purpose of this paper is to examine the effect of cultural difference and travel motivation on event participation and how cultural difference may influence the relationship between travel motivation and event participation. The paper highlights the importance of culture in tourism research. Design/methodology/approach The research was conducted by using a secondary data set ( n =24,692) commissioned by Destination Canada (formerly the Canadian Tourism Commission). Both descriptive statistics (e.g. frequency analysis) and inferential statistics (e.g. hierarchical regressions) were calculated. Findings First of all, the results indicated that travel motivations and cultural difference can impact event participation. For example, those who were more motivated by knowledge and competence (e.g. knowing history and culture) were more likely to participate in art festivals and cultural events. Also, the research recognized that Asian-Canadians were more likely to visit ethnic or religious festivals than Anglo-Canadians, whereas Asian-Canadians were less likely to attend farmers’ market in comparison with Anglo-Canadians. Last, the effect of cultural difference can moderate the relationship between travel motivation and event participation. Originality/value These findings emphasize that travel motivations and cultural difference are key factors to be considered for festivals’ marketing. Particularly, the moderating effect of cultural difference reinforces that the important role played by culture for effective festival marketing should not be ignored. The research also provides valuable insights for destination managers who are interested in Asian markets. Moreover, using a secondary data set prepared by the Canadian Government largely increased the results’ representativeness, trustworthiness, and generalizability.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".