THE NEED FOR BUSINESS MODELS IN ACCESSIBLE, INCLUSIVE AND SUSTAINABLE TOURISM
Bibliographic record
Abstract
Objective: Accessible, Inclusive and Sustainable Tourism has gained significant prominence, reflecting a growing global awareness of the need for inclusive and environmentally responsible travel practices. The literature gap found regarding the absence of a comprehensive business model is the main goal of this research. Theoretical Framework: This study systematically compiled and evaluated the recent research studies on Accessible, Inclusive and Sustainable Tourism to contribute to the evolution of business models in the broader scope of tourism and tourism services. Method: A three-step process was followed to achieve this goal, comprising an initial research phase and a detailed performance analysis using various bibliometric techniques and visualisation tools, culminating in carefully selecting pertinent articles. Results and Discussion: The study confirmed the scarcity of articles that address this topic, with a tendency to conceptualise entirely new business models instead of adapting existing frameworks with new value propositions making them more accessible, inclusive, and sustainable. Research Implications: The practical and theoretical implications of this research provided insights into how the results can be applied or influence practices in the field of tourism. These implications could encompass all tourism areas, from hospitality to restaurant offers. It presents an important managerial clue to guarantee the tourism businesses' true inclusiveness and sustainable characteristics. Originality/Value: This study contributes to the literature by filling a gap. The relevance and value of this research are its managerial contributions, which confirm the need to incorporate characteristics of accessibility, inclusion and sustainability into any tourism business model.
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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 | 0.018 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.024 | 0.025 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".