The environment and climate change as a primary stakeholder for accommodation suppliers: Stakeholder engagement for Koh Tao and Koh Phi Phi, Thailand
Bibliographic record
Abstract
Abstract This study investigates the potential recognition and engagement of the natural environment as an important factor in strategic investment decisions by accommodation suppliers in a small island context. The investigation, based on empirical data from two Thai islands, Koh Tao and Koh Phi Phi, contributes to the debate if the environment, by focusing on climate change, can be identified as a primary stakeholder for accommodation suppliers. The findings show that strategic investment decisions are influenced by impacts commonly associated with climate change, although a conscious recognition of climate change as a strategic stakeholder or important factor in strategic investment decisions could not be confirmed. Conversely, the element of unconsciousness in the process of recognising climate change in investment decisions sparks questions regarding the degree to which the recognition of business stakeholders requires being a conscious process and if the focus on investments could be another element for stakeholder identification frameworks for businesses.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".