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Record W1540116842

Profiles of 50 major furniture retailers worldwide

2008· preprint· en· W1540116842 on OpenAlexaboutno aff
Ugo Finzi, Stefania Pelizzari, Sylvia Weichenberger

Bibliographic record

VenueRePEc: Research Papers in Economics · 2008
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicManagement, Economics, and Public Policy
Canadian institutionsnot available
Fundersnot available
KeywordsHypermarketMail orderBusinessChinaStock (firearms)CommerceEconomyGeographyMarketingAdvertisingEconomicsArchaeology
DOInot available

Abstract

fetched live from OpenAlex

In 2008, for the first time, CSIL put together the profiles of the world's largest furniture retailers in a CSIL report called "Profiles of 50 major furniture retailers worldwide ". CSIL estimates that currently about 19% of worldwide furniture sales are made by "Major Furniture Retailers" which are covered in the new CSIL report. In this first edition we tried to outline the new challenges of the distribution market at a global level. The report provides rankings by geographical region (North America, Europe, Asia), detailed company profiles, financial data and full contact details on about 120 pages. The Major Retailers listed in our report have headquarters in 13 countries of which 9 are in Europe (Austria, Belgium, Denmark, France, Germany, Netherlands, Spain, Sweden, UK), 2 in North America (Canada and US) and 2 in Asia (China and Japan). To draw a picture as precise as possible we considered Furniture Retail Chains (like Ikea, Rooms To Go), Department Stores (like JC Penneys, Macy's), Hypermarket Chains (like Wal Mart, Bailing Group), E-commerce, Mail Order specialists (like Otto Group) and DIY Stores (like B&Q). The report does not include furniture retailer specialised exclusively in office furniture. The total number of profiles included in the report is 54 (25 in Europe, 23 in North America and 6 in Asia). Information in the profiles includes: (i) data provided by the retailers to CSIL during interviews, during the preparation of other CSIL reports and in the course of current research work; (ii) data in company reports, particularly for companies listed on stock exchanges; (iii) information from catalogues, public relations material and websites; (iiii) sector magazines.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.037
GPT teacher head0.282
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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