MétaCan
Menu
Back to cohort
Record W2788081578 · doi:10.7202/1043075ar

Différencier les contributions des filiales d’une multinationale en matière d’innovation

2018· article· fr· W2788081578 on OpenAlexvenueno aff
Mathias Guérineau, Sihem Ben Mahmoud‐Jouini, Florence Charue‐Duboc

Bibliographic record

VenueManagement international · 2018
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Le renforcement du rôle des filiales dans la stratégie d’innovation de la Firme Multinationale (FMN) est souligné par différents travaux. Nous proposons quatre idéaux types différenciés de la contributions des filiales dans cette stratégie à partir d’un cadre analytique qui prolonge celui de Bartlett et Ghoshal (1989) et de l’étude du cas d’une FMN emblématique. Parallèlement aux « grandes historiques » et aux « implémenteurs », deux nouveaux types sont mis en avant; les « accélérateurs » et les « forts potentiels » qui développent des innovations susceptibles d’être déployées dans le reste de la FMN. Le type d’innovations que chaque type de filiale serait le plus à même de développer est également précisé.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.773
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.005

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 head0.020
GPT teacher head0.262
Teacher spread0.243 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueManagement internationalSame topicInternational Business and FDIFrench-language works237,207