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Record W1758524552 · doi:10.7202/1027870ar

La coordination des relations intra- et inter-organisationnelles au sein de l’usine mondiale : le cas Renault Trucks (groupe Volvo)

2014· article· fr· W1758524552 on OpenAlexvenueno aff
Christopher Melin

Bibliographic record

VenueManagement international · 2014
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsFactory (object-oriented programming)HumanitiesPolitical scienceArtComputer science

Abstract

fetched live from OpenAlex

Cet article porte sur la coordination des relations intra- et inter-organisationnelles des firmes multinationales (FMN) dans le contexte de l’usine mondiale (global factory), qui constitue une forme particulière de l’entreprise-réseau. Elle s’appuie sur une recherche-action menée auprès de Renault Trucks (groupe Volvo). L’étude empirique est fondée sur 48 entretiens complétés par des données secondaires. Les résultats obtenus mettent en avant le rôle prépondérant de la firme-pivot dans le pilotage des relations avec les partenaires internationaux. Selon la configuration du partenaire (niveau d’autonomie opérationnelle et fréquence de la transaction), il est recommandé de choisir des mécanismes de coordination spécifiques.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.014
GPT teacher head0.241
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations8
Published2014
Admission routes1
Has abstractyes

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