Implementing a business strategy with supply chain management in a management system and management control to improve the performance of the hotel business
Bibliographic record
Abstract
Supply chain management is very important in improving the business system in the management sector to improve the regional economy. Based on the hotel business strategy at Lovina Beach by implementing e-payments is very important as a transaction tool starting from purchasing needs or marketing systems to the end of room payments and activities to implement the health protocol for the COVID-19 period. The research was conducted at 100 star hotels on Lovina beach Bali, regarding the importance of the main influence of social capital in driving digitalized payment systems and sharing information with microeconomic theory in improving business performance. The results obtained from simple linear quantitative statistical analysis, based on the r-square value of 63.8%, social capital can encourage electronic payments and knowledge sharing can improve hotel business performance in Lovina Beach Bali Indonesia. Research implications for applying social capital, electronic payments, sharing knowledge in improving business performance during the COVID 19 period and making business strategies to increase consumer confidence in hotels on Lovina Beach Bali.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".