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Record W2996539427 · doi:10.1177/0894486519894759

Family Business Succession: What’s Motivation Got to Do With It?

2019· article· en· W2996539427 on OpenAlexafffundabout
Marylène Gagné, Connor Marwick, Stéphanie Brun de Pontet, Carsten Wrosch

Bibliographic record

VenueFamily Business Review · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsConcordia University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSuccessor cardinalEcological successionFamily businessTransgenerational epigeneticsBusinessPerceptionMarketingDual (grammatical number)ManagementEconomicsPsychology

Abstract

fetched live from OpenAlex

Family businesses represent 80% of global business structures, but the low rate of successful transgenerational succession can have drastic implications for employees and local economies. A 12-year longitudinal study of 89 Canadian family businesses revealed that successors’ confidence and perceptions of incumbent support predicted successor intrinsic motivation to take over the business, which in turn predicted whether the business was successfully transferred 12 years later. Incumbent support and intrinsic motivation mediated the relation between incumbent trust in the successor and successful business succession. This study demonstrates the dual importance of incumbent and successor psychological states in determining succession outcomes.

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)0.004
metaresearch head score (Gemma)0.014
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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.025
GPT teacher head0.244
Teacher spread0.219 · 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

Citations133
Published2019
Admission routes3
Has abstractyes

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