Triple-A strategy: For supply chain performance of Indonesian SMEs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it