Bibliographic record
Abstract
案例企业顾家家居是我国软体家具制造业的头部企业。早在1982年，顾家家居的前身顾家工坊就已成立，以“前店后厂”的形式生产沙发；2000年，顾江生接班推出“顾家品牌”；2006年顾家家居成立。此后的10年间，顾家曾进军建材市场，但投资的失败使顾江生坚定信念：顾家未来只要做好家具这一件事情。顾江生提出“大家居战略”并树立了百亿目标。2016年，顾家家居在上海证券交易所上市。2017年，顾家将战略从“专注家居”调整为“专注软体家居的实业发展与战略投资双轮驱动”，而同年，顾家在资本市场上唯一的大动作就是以自有资金5亿元间接持有恒大地产0.16%的股权，并建立了战略合作伙伴关系。随后的2018年开始，顾家在资本市场收购动作频频：纳图兹（Natuzzi）、班尔奇、居然之家、罗福宾士（Rolf Benz）、Nick Scali、玺堡家居、卡文家居、喜临门……本案例对顾家家居及以上收购的基本信息进行了介绍。学员可以据案例材料分析为何顾家家居转变发展战略？为何从2018年开始密集开展并购活动？为什么选择这几家企业开展并购活动？顾家的并购活动达到目的了吗？这种增长方式未来是否可持续？本案例分析亦对中端品牌发展路径的设计有借鉴价值。
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.121 | 0.040 |
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".