Agritourism, Community Attachment and ContributionTowards Tourism and Community
Bibliographic record
Abstract
The tourism industry has encountered various sustainable development functionalities, and nations seek to develop tourism while conserving nature and its resources. Agritourism strengthens a region’s competitive, cultural, and transformational resources while helping the rural community, economy, and society thrive sustainably. However, few studies have evaluated community attention toward agritourism in developing countries. This study bridges this gap using community attachment through agritourism-based resident perceptions of the economic, social, cultural, and environmental impacts of tourism support and its contributions to resident communities. A partial least squares method under structural equation modelling (SEM) was employed using SmartPLS 3.0. Results reveal that community attachment is significantly correlated with economic, social, cultural, and environmental impacts, which are also significantly associated with tourism support. These impacts were mainly related to contributions to the community, thus confirming all hypotheses except for the cultural implications, which were found to be insignificant. This study will help marketers, professionals, and decision-makers understand and predict the economic, social, cultural, and environmental impacts of agritourism and formulate policies to contribute to its development.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".