Predicting Mountain Hikers' Pro-Environmental Behavioral Intention: An Extension to the Theory of Planned Behavior
Bibliographic record
Abstract
Nature-based recreation activities play a major role in the tourism industry and have provided plenty of opportunities for the protection of natural areas. It is essential to study individuals' behavior during such activities to avoid further damage to natural resources. This study develops a robust model that provides a comprehensive understanding of the formation of individuals’ pro-environmental behavioral intentions among climbers of Mount Damavand national park in Iran. For this reason, we combined theory of planned behavior, value-belief-norm theory, and hierarchical model of leisure constraints to predict individuals’ pro-environmental hiking behavior in outdoor recreation. We used structural equation modeling to test the theoretical framework. A sample of 787 climbers was analyzed. Among the TPB variables, perceived behavioral control showed the strongest association with intention (β=.57). This relationship indicates that if people feel they can have less negative impacts on national resources while hiking, it will result in more environmentally acceptable behavior. Subjective norm has a moderate positive impact on intention. It shows the importance of other people on the individual's behavior. Attitude imposed a small positive effect on intention. Biospheric-altruistic values were not significantly associated with individuals’ ecological worldview while egoistic values had a weak negative influence on individuals’ ecological worldview. Moreover, ecological worldview positively influenced attitude and personal belief. Personal belief (Awareness of Consequences and Ascribed Responsibility) showed a positive association with the TPB variables. Although the data showed a high average score in Awareness of Consequences (Mean= 4.219 out of 5), evidence in Mount Damavand shows that there are a lot of environmental issues (e.g. tons of garbage). National parks' managers need to make sure that their solutions have resulted in the awareness of consequences that make people responsible for pro-environmental behavior. Findings support the hypothesized negative relationship between constraints and all TPB predictors. Providing proper restrooms in campgrounds, parking spaces, and strategies such as controlling the carrying capacity or solutions for removing waste from high altitudes are helpful to decrease the negative impact of structural constraints. In order to decrease intrapersonal constraints, managers should Provide techniques that can make individuals interested in environmental activities such as using environmental celebrations or make movies and documentary about environmental issues. To decrease intrapersonal constraints, national parks' managers should provide solutions that encourage people in activities such as environmental celebrations or making movies and documentaries about environmental issues. Moreover, promoting a culture of environmental protection in mount Damavand reduces interpersonal constraints. Overall, the proposed model improved the explanatory power of the TPB by predicting 64.7% of intention compared to the original TPB that accounted for 63.8% of the variance in intention.
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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".