Bibliographic record
Abstract
尽管可持续发展已成为热门话题，但很少有公司与整个价值链的利益相关者创造共享价值。本案例展示了开云集团的可持续发展战略。开云调整组织结构、设定长期细分目标，并实施创新举措如举办可持续创新大奖、推出环境损益表。可持续创新大奖聚集奢侈品生态系统里的重要参与者，建立开放平台，以提高企业公民和环境保护的意识。环境损益表评估开云对生态的影响并引导集团走向更可持续的采购方案和新材料新技术。然而，这两项创新举措都有其局限性。东西方的文化差异意味着很难在东方文化中复制西方的模式。同时，引入新的管理工具必须克服组织的惰性，平衡各方利益。因此，利益相关者管理显得尤为重要。开云对内平衡集团层面的执行力和品牌层面的自主权，对外则与供应商、非政府组织、投资者和媒体等积极沟通。开云未来应该如何更好地在实现生态目标的同时实现长期可持续增长？
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".