How do Chinese Firms Sustain their Cost Advantage in Labour-Intensive Industries?
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
In the past decade, Chinese firms have been competing aggressively in the world labour-intensive industries and have substantially increased their market share. This study explores the mechanisms Chinese firms employ to develop and sustain their cost advantage in labour-intensive industries. The evidence shows that Chinese firms mainly rely on country-specific factors in the initial stage and cluster-specific factors in the growth stage. They integrate these country- and cluster-specific factors to develop firm-specific resources and capabilities in the mature stage. This integration and the dynamics of these resources and capabilities result in the sustainability of their cost advantage. The findings of this study have important managerial implications for those Western firms that wish to duplicate Chinese cost advantages by setting up manufacturing facilities in China and those that are competing against Chinese firms in the world market.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 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