Bibliographic record
Abstract
在全球制造业竞争格局重塑之际,中国制造业既要抓住历史机遇奠定可持续竞争优势,又要接受疫情带来的冲击,传统的生产方式已难以满足激烈的竞争.商业模式的整合是提升制造业竞争力的方式.企业竞争力的提升离不开供应商间的合作,而供应链上成本信息披露也已成为制造业供应链上协作水平与竞争力的重要途径.因此,分析制造商-供应商关系对成本信息披露具有重要意义.将制造商-供应商关系分为联合依赖、不对称依赖和社会关系嵌入,并研究了这3种关系对成本信息披露的影响机制.结果发现:制造商-供应商关系会影响供应商成本信息披露和制造商成本信息使用;联合依赖和社会关系嵌入对供应商成本信息披露具有显著的促进作用,但不对称依赖只能增加供应商的成本信息含量,不能提高成本信息质量;不对称依赖和社会关系嵌入能够促进制造商成本信息使用程度,但联合依赖对此没有显著影响.该研究对制造商通过“关系”降低成本来提升竞争优势具有重要意义.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".