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Record W4306657289 · doi:10.5539/ijef.v14n12p12

Contributions to Succession in a Family Business from the Perspective of Global University Entrepreneurial Spirit Students’ Survey (GUESSS)

2022· article· en· W4306657289 on OpenAlexvenueno aff
Fabiana Pinto de Almeida Bizarria, Flávia Lorenne Sampaio Barbosa, Fagner Martins Santana, Rogeane Morais Ribeiro, Maria do Socorro Silva Mesquita

Bibliographic record

VenueInternational Journal of Economics and Finance · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsnot available
Fundersnot available
KeywordsEcological successionNormativeConstruct (python library)Family businessPerspective (graphical)Succession planningPsychologySocial psychologySociologyManagementEconomicsPolitical scienceMathematicsLaw

Abstract

fetched live from OpenAlex

Relationship between family support and organizational commitment is investigated, in the attitude of succession in a family business, and, this one, in the succession intention. Therefore, the research operationalizes constructs studied by the Global University Entrepreneurial Spirit Students’ Survey, in a survey with 289 university students from the Federal University in Brazil. Structural modeling showed satisfactory adjustment indices to support the seven hypotheses of the study: family support assumes an important explanatory capacity for the variation of affective commitment (R2=38%), as well as of normative commitment (R2=41%); commitment (affective and normative) assumes an important explanatory capacity for the variation in the succession attitude (R2=49%); and, the suggested relationship between the succession attitude and the succession intention (β=0.775; t=22.772, p=0.000), in addition to being supported, demonstrates the greater explanatory capacity of the predictor construct variation (R2=60%). It was concluded, therefore, that prior planning, with actions that mobilize future family members (successors) can result in the achievement of the longevity of these companies.

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)0.000
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 score0.022
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.013
GPT teacher head0.250
Teacher spread0.236 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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