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Competitive Dynamics in Family Firms: Transactional Versus Communal

2023· article· en· W4385216475 on OpenAlexaff
Isabelle Le Breton‐Miller, Danny Miller

Bibliographic record

VenueAcademy of Management Proceedings · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsDynamics (music)Transactional leadershipTransactional analysisEconomic geographyBusinessIndustrial organizationEconomicsSociologyPsychologySocial psychology

Abstract

fetched live from OpenAlex

Scholars of competitive dynamics have emphasized economic and psychological drivers of rivalry. But in overlooking owner objectives, most have neglected important socioemotional priorities that can shape competitive conduct. Using the example of family firms, a dominant form of enterprise globally, we explore these influences. Drawing on the socioemotional wealth perspective we argue that family firms whose owners prioritize long term generational involvement as a source of socioemotional wealth will favor stakeholder-friendly, socially inclusive communal competition. By contrast, owners favoring current economic benefits for today’s family members will favor more short-term, family oriented transactional competition. We develop propositions differentiating these competitive models in core characteristics, competitive interactions, and repertoires, and draw implications for the classic AMC (awareness, motivation, capability) model of competitive behavior. We conclude that socioemotional priorities manifested by many family firms, require both recontextualization and rethinking of current understandings in competitive dynamics.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.262
Teacher spread0.230 · 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 designQualitative
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
Published2023
Admission routes1
Has abstractyes

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