The effect of supply chain integration on hotel performance through green supply chain management
Bibliographic record
Abstract
Internal and external integration in hotel industries is essential to improve Green Supply Chain Management (GSCM) to maintain hotel performance and sustainability. This research is to examine the impact of internal and external integration on GSCM and hotel performance. It is quantitative research with judgmental sampling. Questionnaires were distributed to 72 hotel employees from 62 hotels of three-star hotels and above, who understand GSCM and hotel performance in East Java. But 66 questionnaires were returned, and only 62 questionnaires were valid for data analysis. Structural Equation Modelling (SEM) is used to analyze with the help of Java Web Start software. The results show that all six hypotheses are supported, internal integration with Use technology to significantly determine plans and coordination capable of external integration and GSCM. External integration with Sharing knowledge with partners and Collaborating in solving problems can improve GSCM significantly. Supply chain integration, which consists of internal integration and external integration, impacts hotel performance by reducing hotel waste and Efficient use of resources. GSCM in implementing Eco green, green procurement and product life cycle have a significant impact on improving hotel 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".