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Record W2077031421 · doi:10.7202/044029ar

Effets modérateurs des capacités complémentaires dans le e-commerce

2010· article· fr· W2077031421 on OpenAlexvenueno aff
Moez Bellaaj

Bibliographic record

VenueRevue internationale P M E Économie et gestion de la petite et moyenne entreprise · 2010
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicBusiness Strategy and Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Si la théorie des ressources a été mobilisée par plusieurs chercheurs pour expliquer la performance du commerce électronique (e-commerce), la complémentarité entre des ressources e-commerce et des ressources organisationnelles complémentaires est cependant peu étudiée. Dans cette étude, nous examinons l’effet d’interaction des capacités e-commerce et des capacités organisationnelles complémentaires sur l’avantage compétitif. Un nouveau modèle a été développé pour tester le rôle de trois modérateurs : orientation client, capacité TI et opportunisme technologique. Après avoir contrôlé les effets du secteur d’activité, de la taille de l’entreprise et de l’expérience Web, ce modèle a été testé sur un échantillon composé de 91 entreprises. Les résultats de l’analyse ont montré la pertinence du modèle proposé qui a expliqué plus de 70 % de la variance du phénomène étudié. Cette recherche a montré qu’une orientation client réactive n’exerce pas une influence positive sur la relation « capacités e-commerce – avantage compétitif », alors qu’une orientation technologique proactive renforce la capacité de l’entreprise de tirer profit du commerce électronique.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.248
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; both teacher heads agree on what is shown here.

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

Citations2
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueRevue internationale P M E Économie et gestion de la petite et moyenne entrepriseSame topicBusiness Strategy and InnovationFrench-language works237,207