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Record W2899332012 · doi:10.1002/cjas.1513

Entrepreneurial orientation and performance in private family firms: A configurational model

2018· article· en· W2899332012 on OpenAlexvenueno aff
Jonathan Bauweraerts

Bibliographic record

VenueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsnot available
Fundersnot available
KeywordsDynamismSocioemotional selectivity theoryEntrepreneurial orientationEntrepreneurshipContext (archaeology)Family businessBusinessPerspective (graphical)Empirical researchMarketingIndustrial organizationManagementKnowledge managementPsychologyEconomicsComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract The relationship between entrepreneurial orientation (EO) and performance has received considerable attention from the family business literature. However, little is known about how EO, organizational parameters, and environmental characteristics act in combination to influence family firm performance. Drawing on the socioemotional wealth perspective, this study proposes a configurational model that considers the performance implications of EO, family management, and environmental dynamism. The empirical analysis indicates that the combination of family management, low EO, and low environmental dynamism engenders the best performance. The paper contributes to the family entrepreneurship literature by identifying the conditions under which EO leads to improved performance in family firms, and answers a recent call for more context‐based investigations of the performance effects of family managers. © 2018 ASAC. Published by John Wiley & Sons, Ltd.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.079
GPT teacher head0.294
Teacher spread0.215 · 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 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

Citations10
Published2018
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l AdministrationSame topicFamily Business Performance and SuccessionFrench-language works237,207