The Emergence of Green Management and Sustainability Performance for Sustainable Business at Small Medium Enterprises (SMEs) in the Culinary Sector in Indonesia
Bibliographic record
Abstract
This study aims to see the emergence of green management and sustainable performance that can affect sustainable business in Small and Medium Enterprises (SMEs) in the culinary sector in Indonesia.This research sample is of 372 SMEs in the culinary sector in Indonesia.Data analysis uses factor analysis and partial least squares (PLS).The sampling technique used stratified cash based on UNWTO (2012) criteria.The results showed that stakeholder demand has a significant effect on the implementation of green management, resources and knowledge have a significant effect on the implementation of green management.It shows that stakeholder demand, available resources, knowledge, and product uniqueness significantly affect green management.Product uniqueness has a significant effect on green management, and green management has a significant effect on sustainability performance.Green management simultaneously has a significant effect on sustainability performance.The research innovation is a green management and sustainability guidelines for SMEs culinary sector to implement and improve green management and sustainability performance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".