Do community entrepreneurial development shape the sustainability of tourist villages?
Bibliographic record
Abstract
This study looks at the role of community entrepreneurial development in mediating the linkages between geographical conditions, local wisdom, and traditional culture on the sustainability of tourism villages. In this study, this hypothesis was evaluated quantitatively. Respondents filled out a questionnaire as a research instrument. Village officials, the Tourist Awareness Group (Pokdarwis), and the community in Cikolelet Tourism Village, Banten Province, participated in this research. 140 individuals were selected for this study using purposive sampling, and the data were analyzed using a structural equation model (SEM). According to the conclusions of this study, geographical conditions, local wisdom, and traditional culture have a beneficial and statistically significant influence on community entrepreneurial development but do not directly affect the sustainability of tourism villages. Community entrepreneurial development influences the sustainability of tourist villages. Furthermore, community entrepreneurial development mediates the relationship between geographical conditions, local wisdom, and traditional culture on the sustainability of tourist villages. These findings recommend that tourism stakeholder cooperation between village officials, the Tourist Awareness Group, and the community must collaborate in the sustainability of the tourist village. This paper offers novelty by investigating community entrepreneurial development variables as mediators of the influence of geographical conditions, local wisdom, and traditional culture on the sustainability of tourist villages with exploratory quantitative analysis. In contrast, previous research only used explorative qualitative analysis, at least in the tourism sector, from an Indonesian perspective.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".