Bibliographic record
Abstract
This case demonstrates how, through trial and error, Qingdao Kutesmart Co., Ltd. ("Kutesmart," formerly known as Qingdao Red Collar Group Co., Ltd.) executed its strategy of "building a customer-to-manufactory (C2M) business ecosystem," following transformation from mass production to mass customization. In 2015, Kutesmart launched Magic Manufactory to explore consumer-oriented garment customization. However, when public response fell below expectations, the new brand closed its physical stores in the second half of 2016. Drawing on the lessons learned from the failure of Magic Manufactory, Kutesmart launched Cotte Yolan, a proprietary made-to-measure garment brand designed by founder Daili Zhang with an eye on handing over the reins to daughter Yunlan Zhang. To ensure a successful succession, Daili, who was about to retire, formulated Cotte Yolan's own governance framework and carried out a range of organizational changes. He believed that with this governance system, companies in other industries could also transform to customization and succeed in succession. Looking ahead, father and daughter had different views regarding the future position of Cotte Yolan: should it be a fashion brand, a made-to-measure garment supplier, or a project to promote the transformation and upgrade among traditional companies? In addition, would Cotte Yolan's governance framework prove crucial for implementing Yunlan's C2M strategy and leading the company into the future?
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".