Rural Tourism Sustainable Management and Destination Marketing Efforts: Key Factors from Communities’ Perspective
Bibliographic record
Abstract
Rural tourism is seen as a potential sector in promoting country to the world and at the same time generates incomes to local communities. However, due to the lucrative economic benefits, tourism destination’s sustainability and quality of services is often being ignored. Thus, this study highlights the importance of sustainable management and destination marketing efforts in rural tourism destinations with identified significant contributively factors from local communities’ perspective. A total of 168 respondents comprising of local communities from <em>Kampung Telaga Air</em> and <em>Kampung Semadang</em>, Kuching, Sarawak took part voluntarily in this study. To assess the developed model, SmartPLS 2.0 (M3) is applied based on path modelling and bootstrapping. Interestingly, the findings revealed that local communities believed factors like climate change, carrying capacity of a destination, and environmental education are significantly affect both tourism destination sustainable management and destination marketing efforts. Furthermore, community support is also found to be important too for tourism destination marketing efforts. Surprisingly, community support was found no relations with destination sustainable management from local communities’ point of view. This study further discussed on the implications of the findings, limitations, and direction for future research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".