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Record W3021697599

IMPACT DU CAPITAL SOCIAL ENTREPRENEURIAL SUR LA PERFORMANCE ET L’ACCÈS AUX RESSOURCES EXTERNES : REVUE DES ÉCRITS

2020· article· fr· W3021697599 on OpenAlexaboutno aff
Nour El Houda Mokhtari, Abdelkader Maaroufi, Najib Tirou

Bibliographic record

VenueInternational Journal of Economics and Management Research · 2020
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

Les etudes sur la performance des entreprises occupent une place importante dans les travaux fondamentaux de beaucoup de chercheurs en sciences economiques et de gestion.   Cependant les avis et les resultats sur les impulsions sociales de la performance des entreprises restent divergents. Ainsi, par exemple, les developpements menes par Nkakleu (2003) revelent que les entreprises, dont les dirigeants, ont des liens sociaux plus nombreux fonctionnent mieux, sont plus performantes que celles dont les liens sociaux des dirigeants le sont moins. Les travaux menes par Baillette (2001) aupres du groupement des chefs d’entreprises du Quebec revelent que le capital social developpe par ces dirigeants leur a permis d’acceder a des sources informationnelles tres riches et a d’autres ressources variees. Dans la meme lancee, Plociniczak (2004) affirme que « l’analyse de la creation d’entreprises, et plus generalement, de l’action economique ne peut se passer d’une integration pleine et effective des cadres relationnels et des structures institutionnelles sans lesquels elle ne pourrait se deployer » (Plociniczak, 2004, p.1-37). Le present article se propose de montrer l’impact de la prise en compte du capital social sur le processus de construction de la performance des entreprises, afin de donner une impulsion de reconsideration de la place des rapports humains et sociaux aux dirigeants dans la construction de leurs performances.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.094
GPT teacher head0.326
Teacher spread0.232 · 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
Published2020
Admission routes1
Has abstractyes

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