Environmental management in slovenian tourist enterprises
Bibliographic record
Abstract
The attitudes towards the natural environment and its uses are becoming an issue of global concern.Climate change and the associated natural disasters have created a demand for different practices in the use of natural and environmental goods in a more long-term, sustainable way to reduce the damage caused by different economic and human activities.Such activities also include leisure and tourist activities where the focus should be on sustainable tourism development to strike a balance between economic interests and ecological requirements.The EU has adopted and implemented programmes for sustainable development where special support is devoted to the sustainable economic development of different economic activities.Considering the level of economic development and Slovenia's membership in the EU since 2004, it is surprising that in the field of tourism there is only one certified enterprise or product with the EU Eco-label in Slovenia.This is even more striking if we consider the fact that ecological policies have already been implemented at the government level for few years and that based on the rate of biodiversity Slovenia is among the richest regions of the EU (Natura 2000).There are specific ecological programmes to protect the environment, but few in the field of tourism in comparison to some other EU countries.So far, there is only one registered tourist enterprise 'Spa Snovik' near Kamnik in Slovenia that is certified with the Eco-label.Moreover, 'Spa Radenci' and 'Spa Snovik' are the only tourist suppliers with the ISO 14001 certificate for the integrated management of the environment.In this study, we aim to explain why Slovenian tourist suppliers are reluctant to introduce standards with eco-labels and other ecological symbols.We analyse the costs and benefits of environmental management in tourist enterprises by considering the importance of brand name and image building, which are important for competitive position in tourist markets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".