Triple-A strategy: For supply chain performance of Indonesian SMEs
Bibliographic record
Abstract
Supply chain management is an activity that effectively integrates suppliers, companies, retailers where goods are produced and distributed at the right quality, location, and time with minimum cost levels to provide the highest quality services for consumers. Supply chain agility, supply chain adaptability, supply chain alignment, which is known as the Triple-A strategy, are elements to form supply chain performance. In this study, we tried to apply it to SMEs in developing countries, such as Indonesia. The purpose of this study is to show whether it is true that the supply chain cannot be applied to SMEs, while for a disruption as it is today, competition is getting tougher not only among SMEs but also against large companies, and SMEs need to develop several strategies that were previously unimaginable. This study uses quantitative techniques to determine the effect of supply chain agility, supply chain adaptability, supply chain alignment on supply chain performance either partially or simultaneously. The results showed that all hypotheses were accepted. This shows that supply chain management can be a strategy to create better SMEs performance and can even be used to achieve competitive advantage.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".