Bibliographic record
Abstract
The Top 200 furniture manufacturers worldwide report provides an overview of the furniture competitive system, selecting and listing 200 furniture top companies by their revenues, products and geographical coverage. Data on global furniture consumption, trade and production are included for time frame 2011-2016. Comparisons between industry trends and top furniture manufacturers are provided. Top 200 manufacturers are broken down and analysed according to headquarters location, activity and furniture product specialization (office, kitchen, home and upholstered furniture) as well as financial performance (turnover and employment). Profiles are structured with the following information: Companies directory (headquarters address, telephone number, website, email address, year of establishment), Business activity (product portfolio, furniture product specialization), Financial performance (total revenues and number of employees), Manufacturing activity (facilities location, plant expansion and cost rationalization strategies), Sales breakdown by product and by geographical area, Distribution activity: brands, retailing and branding strategies for the domestic and international markets. Companies selected have headquarters in the following countries: Australia, Austria, Azerbaijan, Brazil, Canada, China, Denmark, Finland, France, Germany, Hong Kong, India, Italy, Japan, Liechtenstein, Lithuania, Malaysia, Netherlands, Norway, Poland, Romania, Russian Federation, Singapore, South Africa, South Korea, Sweden, Switzerland, Taiwan, Turkey, United Kingdom, USA.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.188 | 0.138 |
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".