Upgrading in the Global Clothing Industry: Mavi Jeans and the Transformation of a Turkish Firm from Full‐Package to Brand‐Name Manufacturing and Retailing
Bibliographic record
Abstract
Abstract:Since 1984, Erak Clothing, a Turkish contractor, has manufactured jeans as a full‐package producer for international brands, such as Calvin Klein, Guess, and Esprit. Following the creation of its own brand, Mavi Jeans, in 1991, the firm has been transforming itself into an original brand‐name manufacturer and retailer. Mavi Jeans are now sold worldwide at more than 3,000 sales points, including Nordstrom, Macy's, and Bloomingdale's department stores, and five directly owned and operated flagship stores in Vancouver, New York, Frankfurt, Berlin, and Montreal. In this article, the authors tell the exceptional story of the firm's transformation from a full‐package manufacturer into an original brand‐name manufacturer and retailer. They discuss how a peripheral manufacturing firm has managed to achieve a high value‐added competitive advantage by gaining access to global networks of production, consumption, and information in the clothing industry: a buyer‐driven industry in which the world's largest retailers, branded marketers, and manufacturers without factories are the dominant players with asymmetrical influence and power. The case study supports the theoretical position that individual firms have some room for autonomous action and that power relationships have some fragility that can be exploited by firms with strategic intent.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".