The effect of manufacturing agility competencies on lean manufacturing in increasing operational performance
Bibliographic record
Abstract
This study aims to assess the success of implementing Lean Manufacturing (LM) practices in food companies in Indonesia through the mediating role of Manufacturing Agility Competencies (MAC) to improve Operational Performance (OP). The method used is survey method. The study uses a positivist paradigm to see the effect of Lean manufacturing on operational performance. Testing used Structural Equation Modeling (SEM) by the Partial Least Square (PLS) approach. Finding of this study reveals that lean manufacturing practices have no positive effect on operational performance in Indonesian food industries. Meanwhile, the mediating role of Manufacturing Agility Competencies has succeeded in increasing the effect of Lean Manufacturing on operational performance. The originality of the research lies in the process of forming Manufacturing Agility Competencies as a strategy with a long process based on the experiences and observations made in food companies in Indonesia.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".