Understanding coffee tourism development through the dynamic capabilities lens: a qualitative cross-national exploration
Bibliographic record
Abstract
This research contributes to a deeper empirical and conceptual understanding of coffee tourism development. By using a qualitative cross-national approach encompassing five coffee producing nations and guided by the dynamic capabilities framework, this study examines the potential, capitalisation and further consolidation of coffee tourism. The experiences of coffee firm leaders were gathered through semi-structured open-ended interviews; the qualitative analysis uncovered 12 overarching dimensions and helped craft a conceptual framework, with implications for understanding coffee tourism development from a practitioner and conceptual perspective. For instance, coffee tourism's potential is mainly explained by the visitor-centred and firm-centred dimensions, while the individual firm and upstream supply-chain capitalisation dimensions illuminate capitalisation demonstrations. The findings also exhibited relationships with the dynamic capabilities framework. Among these, educational experiences elucidate coffee tourism's potential (sensing) the capitalization of financial gains (seizing) while working alongside the government underlines further tourism development (reconfiguring). Various differences were also noted between countries and regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".