Assessing the sustainability of tourism products – as simple as it gets
Bibliographic record
Abstract
The balance between the three dimensions of sustainability forms the basis for the successful development of a tourism region.The development of sustainable products is crucial for a destination in order to create true sustainable experiences for their guests.The research project aimed to determine the criteria for sustainable tourism and to develop a simple method for the sustainability assessment of tourism products.While most valuation methods require the presence and the analysis of a comprehensive data set, the assessment tool should enable the destination to analyse the sustainability of their products as easily as possible.Together with five Swiss tourism destinations an assessment tool was developed and tested.In a first step, the central sustainability criteria for tourism products were defined based on existing criteria sets.Then an inventory of all tourist products was created.Every single product was quantitatively assessed with regards to the sustainability criteria by the project manager of the destination management organisation (DMO).Their experiences were evaluated through qualitative interviews.The sustainability assessment using the framework showed various challenges such as the dependence of the prior knowledge of the evaluator.The variety of the products also hampers a consistent assessment and a comparison between destinations.The strengths of such a simplified model are that it allows a comparison to changes of sustainability in the product portfolio over time.In addition, it promotes the internal discussion and awareness.Using the new framework during the development of new products helps to take all criteria into account.It also supports the connection with service providers and the communication of sustainability requirements.The instrument tested represents a compromise that reduces complexity and enables the assessment of sustainability without the use of a comprehensive monitoring system -as simple as it gets.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".