Bibliographic record
Abstract
本案例聚焦传统制造业企业在新的行业环境下所面临的挑战及战略选择问题。案例企业特地陶瓷是一家位于佛山的中等规模的瓷砖公司。2014年特地与同样起源于科达系的品牌“欧神诺”彻底分开。此时中国建筑陶瓷市场已经不再是其2004年创立时快速增长的态势，产能过剩和产品同质化导致竞争激烈，行业极度分散。瓷砖的销售模式也从最初的经销制转变为与地产商结成战略合作关系。特地既没有很高的知名度，又没有可以一直为地产商垫资的实力，该怎样走出一条差异化的道路呢？ 本案例复盘了特地陶瓷依托其负离子瓷砖技术，另修“赛道”的战略变革过程。董事长冯红健、掌舵人李强将特地品牌全面升级为“特地·负离子瓷砖”，将传统店面升级为体验馆、负离子科技馆，培训和升级经销商团队，开发设计师渠道，进行客户回访、口碑营销，升级产品并建立强大的后台体系。这些举措帮助特地在更名后的第一年实现了37%的高增长。 面向未来，特地设置了三年内业绩翻番的目标，而摆在特地面前的路有三条：深耕功能性瓷砖市场、利用负离子陶瓷技术开发多品类陶瓷产品、跨界进入大健康产业。特地又应该做何选择呢？
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.011 | 0.023 |
| Scholarly communication | 0.021 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 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".