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Record W4308983962 · doi:10.1108/jfbm-06-2022-0076

Family governance and firm performance: exploring the intermediate effects of family functioning and competitive advantage

2022· article· en· W4308983962 on OpenAlexaff
Francesco Barbera, Tim Hasso, Thomas Schwarz

Bibliographic record

VenueJournal of Family Business Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCorporate governanceOriginalityCompetitive advantageBusinessFamily businessExtant taxonAffect (linguistics)Value (mathematics)Perspective (graphical)Industrial organizationMarketingKnowledge managementPsychologySocial psychologyFinanceComputer science

Abstract

fetched live from OpenAlex

Purpose Scholars and practitioners agree that governance practices are at the core of what differentiates family firms from other forms of business. Yet, there is a lack of consensus in the extant literature about how and the extent to which family governance affects firm performance. This study aims to address the matter by taking a more comprehensive unified systems perspective to explore the pathways through which variations in family governance mechanisms simultaneously affect both the business and the family system. Design/methodology/approach This study utilises a global dataset sourced from a survey and structural equation modelling to empirically measure several intermediate and final outcomes of family governance. Findings This study finds that the use of family protocols, as well as formal and informal meetings, have positive effects on the functioning of the family, whereas family involvement in the top management team diminishes the firm's competitive advantage. In turn, this study demonstrates that both family functioning and competitive advantage are positively related to firm performance. Originality/value By taking into consideration the complexity of the family and business systems, and measuring their interlinkages, this study advances knowledge by providing a more complete picture of the family governance/firm performance relationship.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.003
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 head0.017
GPT teacher head0.212
Teacher spread0.194 · 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

Citations11
Published2022
Admission routes1
Has abstractyes

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