Social entrepreneurship in tourism: A framework-based scoping review and research agenda
Bibliographic record
Abstract
While tourism social entrepreneurship (TSE) has been gaining the interest of tourism scholars, little is known about the extent of knowledge on TSE and how understanding this phenomenon may be advanced. To address these gaps, we conducted a framework-based scoping review of academic publications ( N = 190) on this topic published from 2006 to 2023. We operationalised Gartner's (1985) framework for new venture creation comprising four dimensions namely individuals , organisations , environment , and processes , which we have extended to include a fifth dimension on impacts to further reflect the societal value of TSE. We found that knowledge of TSE is centred on processes , indicating a strong focus on the supply side of this tourism development approach and signalling critical knowledge gaps especially on individuals and impacts of TSE. We propose a conceptual model that shows the complexity and multidimensionality of TSE. Finally, we contribute a research agenda to advance knowledge of TSE.
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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 | 0.037 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.047 | 0.037 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".