A resource‐based view of manufacturing strategy and the relationship to manufacturing performance
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
Abstract This paper examines manufacturing strategy from the perspective of the resource‐based view of the firm. It explores the role of resources and capabilities in manufacturing plants that cannot be easily duplicated, and for which ready substitutes are not available. Such resources and capabilities are formed by employees' internal learning based on cross‐training and suggestion systems, external learning from customers and suppliers, and proprietary processes and equipment developed by the firm. Based on data from 164 manufacturing plants, the paper empirically demonstrates that competitive advantage in manufacturing (as measured by superior plant performance) results from proprietary processes and equipment which, in turn, is driven by external and internal learning. The implication is that resources such as standard equipment and employees with generic skills obtainable in factor markets are not as effective in achieving high levels of plant performance, since they are freely available to competitors. The paper also demonstrates the important role of internal and external learning in developing resources that are imperfectly imitable and difficult to duplicate. Copyright © 2002 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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