Determinants of Canadian and US mountain bike tourists’ site preferences: examining the push–pull relationship
Bibliographic record
Abstract
The purpose of this research was to examine the travel behaviors, travel motivations, and site preferences of Canadian and US mountain bikers to better understand the determinants of destination attractiveness during mountain bike-specific travel. An online questionnaire was distributed through social media of Canadian and US mountain bike clubs to collect data. A total of 1346 responses were collected, however, responses with missing data or from outside of Canada and US were deleted, resulting in a sample of N = 720. Data were analyzed using descriptive statistics, exploratory factor analysis (EFA), and multiple regression analysis. EFA analysis of the 41 pull items extracted seven pull factors consisting of climate, trail conditions, natural setting, information sources, trail features, tourism infrastructure, and entertainment options. EFA analysis of the 20 push items extracted five push factors comprised of stimulus-avoidance, adventure experiences, novelty, competency-mastery, and social encounters. Multiple regression analysis revealed that push factors were correlated with pull factors, indicating that travel push motives and destination pull factors interact to form a mountain bike tourists’ perception of destination attractiveness. The findings offer recommendations for developing and marketing a mountain bike-specific travel destination.
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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 | 0.004 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".