Value chain analysis of total quality control, quality performance and competitive advantage of agricultural 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
This study aims to examine the contribution of the application of total quality control in improving quality performance and its consequences for the creation of competitive advantage. The research method used is a verification survey method to describe the empirical conditions of the production process activities at SMEs producing cocoa in Central Sulawesi Province. The analytical tool used is path analysis with a two-stage regression approach to examine the structural relationship between variables. The results show that total quality control consisting of employee empowerment, employee training and teamwork culture had a significant effect on improving the quality performance of cocoa SMEs. The consequences of improving quality performance are proven to mediate employee empowerment, employee training, and a culture of teamwork in creating a competitive advantage for cocoa SMEs in Central Sulawesi Province.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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