Active event sport tourism experience: the role of the natural environment, safety and security in event business models
Bibliographic record
Abstract
The connection between tourism development and the natural environment is more intense in outdoor sport tourism than in many other forms of tourism. Natural settings (space), sport activities undertaken and the motivations of the people who participate in them interact to create sport tourism experiences. Tourist safety and security are also proved to be important elements of a tourist experience and it seems that sport tourists may be more sensitive to safety issues than non-sport tourists. This paper therefore aims to analyse the importance of the natural environment and safety and security issues, as constitute event business model elements, in providing sport tourism experiences. The natural setting is also examined as a motivation to participate in sport tourism travel. On the basis of 464 questionnaires gathered from active participants of 16 small-scale sport events in four different outdoor sports, exploratory factor analysis was conducted on motivational statements and revealed a conceptually clear sevenfactor structure. One of them, titled 'Nature', was the second most important motivational dimension for participants but differences between particular sports were considerable. In terms of business model elements included in the survey, participants gave high importance to all elements related to the natural environment and safety and security. Scenic destination, scenic and interesting course, course safety and event safety were the most important elements of event business models for participants in all four sports. Environmental management and proper implementation of security and crowd control measures were also singled out as important event processes. However, results of ANOVA indicate statistically significant differences between the sports in seven out of nine business model elements. These findings shed some light on the managerial aspects of sport tourism practice, helping managers to better serve sports and tourism needs at a particular event and in the 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 | 0.001 | 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".