Innovation and Entrepreneurship : strategies and processes for success in tourism
Bibliographic record
Abstract
Innovation – The story behind success in Tourism \nTourism demand is becoming very volatile. In addition financial crisis and hyper competition in the liberalised world market worsen the situation. To survive entrepreneurs have to continuously adapt to changes, improve services, create new products and break into new markets. In short: They have to be innovative. \n \nThis volume provides you a unique inside view of innovative entrepreneurs in tourism who had the foresight to transform their practices in the tourism industry in an almost revolutionary fashion, e. g.: \n \nG.A.P. Adventures, Canada \nTouring Cars Finland LTD, Finland \nJoska Kristall, Germany \nthe Sextantio Albergo Diffuso, Italy \nthe Spas of Salt Mine Bochnia, Poland \n \nThese stories of innovation and entrepreneurship in tourism from 13 countries exemplify the key factors for introducing new tourism products and processes successfully.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".