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Record W2007644055

Behavioral Outcomes of Next Generation Family Members’ Commitment to Their Firm

2014· article· en· W2007644055 on OpenAlexaffabout
Alexandra Dawson, P. Gregory Irving, Pramodita Sharma, Francesco Chirico, Joel Marcus

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsYork UniversityWilfrid Laurier UniversityConcordia University
Fundersnot available
KeywordsTransformational leadershipRespondentGeneralizability theoryOrganizational commitmentPsychologySocial psychologyNormativeContext (archaeology)Public relationsPolitical scienceDevelopmental psychology
DOInot available

Abstract

fetched live from OpenAlex

Are there variations in behaviors and leadership styles of next generation family members or descendants who join their family business due to different forms of commitment? Evidence from a dual respondent study of 109 Canadian and Swiss family firms suggests that descendants with affective commitment to their family firms are more likely to engage in discretionary activities going beyond the job description, thereby contributing to organizational performance. Next generation members with normative commitment are more likely to engage in transformational leadership behaviors. Both affectively and normatively motivated next generation members use contingent reward forms of leadership. A surprising finding of this study is the binding force of normative commitment on positive leadership behaviors of next generation members. This study empirically tests the generalizability of the three-component model of commitment to family businesses, a context in which different forms of commitment may play a unique role.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.166
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.083
GPT teacher head0.285
Teacher spread0.202 · 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.

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

Citations3
Published2014
Admission routes2
Has abstractyes

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