How the Fashion and Luxury Industry challenges the Crisis by Redesigning Value Chains
Bibliographic record
Abstract
The fashion and luxury industry is part of the Made in Italy fashion system that represents an important constituent of the Italian industrial system, where Italian apparel sector represents 7.1% of the national manufacturing industry turnover, with 516,700 employees, 59,750 firms and total revenues of 52,835 million euro in 2006. However, the industry turnover has been -15.1% in the first quarter of 2009, due to the global crisis and fierce low labour cost country competition. This research project aims at studying Italian fashion and luxury apparel firms to: understand how companies can react to the current crisis in order to remain competitive; to explain how companies can redesign their value chain to improve their efficiency; and to evaluate new managerial and organizational models that support business development. The multiple-case study method is adopted to investigate these research questions. We conducted 12 in-depth case studies using a semi-structured interview protocol specifically designed for this research.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".