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Record W2055690164 · doi:10.7202/1008425ar

La gestion du changement technologique dans la PME manufacturière au Québec : une analyse de cas multiples

2012· article· fr· W2055690164 on OpenAlexaffvenueabout
Pierre‐André Julien, Jean-Bernard Carrière, Louis Raymond, Richard Lachance

Bibliographic record

VenueRevue internationale P M E Économie et gestion de la petite et moyenne entreprise · 2012
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

L’objectif de cette recherche, effectuée auprès de 14 PME manufacturières québécoises, visait à identifier différents types ou « styles » de gestion du changement technologique à partir d’une grille d’analyse comprenant quatre dimensions : les avantages stratégiques perçus par !’entreprise, la qualité de son processus décisionnel, ses capacités organisationnelles et ses compétences technologiques. L’analyse a permis de dégager un portrait général illustrant certaines caractéristiques communes à toutes les entreprises visitées. De plus, une analyse typologique a permis d’identifier au moins trois types ou styles de gestion du changement technologique mettant en relief les caractéristiques différenciant les entreprises entre elles. Les différences les plus marquées entre les trois types ou styles de gestion de changement technologique touchent la qualité de la veille commerciale, l’envergure des changements technologiques effectués ainsi que la position technologique et concurrentielle des entreprises. De plus, le rythme d’adoption des technologies, la qualité de la veille technologique et l’importance des ressources humaines et financières allouées par les entreprises à la R-D contribuent le plus fortement à distinguer les trois types entre eux.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.241
Teacher spread0.226 · 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 designObservational
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
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueRevue internationale P M E Économie et gestion de la petite et moyenne entrepriseSame topicInnovation and Knowledge ManagementFrench-language works237,207