The influence of supply chain quality integration on operational performance through innovation quality integration
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
Sanitary and product manufacturing companies' care in Indonesia is increasingly challenging to carry out production due to limitations caused by the lockdown during the pandemic. The conditions demanded very high and required fast distribution mobility. The company maintains product quality by established standards according to specifications, but the production process time is limited. To maintain product quality, companies must retain supply chain quality integration and innovation quality integration to support Operational Performance. The research uses manufacturing companies focusing on plastic companies with bottle and tube production related to supply packaging health protocol products. Analysis to answer the research hypothesis uses the software SmartPLS. The study results found that internal supply chain quality integration by integrated manufacturing processes positively and significantly affects supplier and customer quality integration. Supply chain integration, which consists of supplier quality integration, internal quality integration, and customer quality integration, impacts increasing product innovation and the number of new products. Supply chain quality integration and innovation quality integration directly influence operation performance. This research enlightens company managers on improving internal capabilities and establishing synergy with suppliers and customers to create innovation, aiming to increase operational performance to compete with the global market and face market fluctuations. Research makes a theoretical contribution to quality development and supply chain integration.
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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 | 0.003 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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