The Impacts of Multi-environmental Constructs on Tourism Destination Competitiveness: Local Residents’ Perceptions
Bibliographic record
Abstract
In the rural tourism industry, the environment has emerged to be of most concern to the local communities, followed by social-cultural and economic issues. Stemming from the awareness, the environment has become one of the main pillars for sustainable tourism development, particularly, rural tourism destination. On the other note, in a competitive tourism market, it is important for rural tourism destinations to create competitive advantage in order to attract visitors. Therefore, competitiveness theory underpins the research framework proposed and attempts to examine the impacts of multi-environmental constructs towards the development of rural tourism destination competitiveness. A total of 278 respondents comprising of local communities from rural destinations in Sarawak, Malaysia took part voluntarily in this study. To assess the developed model, SmartPLS 2.0 (M3) is applied based on path modelling and bootstrapping. The findings showed that local residents are in their believed that for a rural tourism destination to enhance its competitiveness, environmental education is the key to increase environmental conservation that lead to better quality of environment. Tourism infrastructure is an added advantage to increase a tourism destination competitiveness. 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| 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".