(Un)willingness to pay to visit a national park from a sustainable entrepreneurial tourism perspective
Bibliographic record
Abstract
As the number of protected areas increases in a country, there is a need for entrepreneurial action to maximize the environmental and economic benefits of nature-based tourism and to complement government funding. Establishing an entrance fee to visit these protected areas could be a good option to ensure long-term economic sustainability. Therefore, using Herzberg's theory of motivation-hygiene and the fuzzy-set qualitative comparative analysis methodology (fsQCA) as a valid theoretical framework, this study aims to analyze the combined effects of both motivating and hygiene variables which lead to the absence of willingness to pay (WTP) an entrance fee to visit a national park. The findings indicate that motivating factors, such as prior visits to other national parks, the inclination to visit a national park, or a strong commitment to environmental issues, were more important than hygiene factors, such as value for money and overall satisfaction with the visit. Managerial implications and directions for future studies are also discussed. • New forms of financing should be explored to manage natural parks. • Motivating factors are more important than hygiene factors to affect visitors' WTP. • Visitors' habits play a key role in explaining the visitors' WTP. • Satisfaction with the visit plays a secondary role in explaining the visitors' WTP. • No differences between men and women in the intention to pay or not an entrance fee.
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 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 | 0.008 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".