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Record W1926080849 · doi:10.5539/ass.v11n24p1

Research on Cohesion of Top Management Team of Family Enterprises: A Review Based on Conflict Management

2015· review· en· W1926080849 on OpenAlexvenueno aff
Yongwen Lu, Jie Lü

Bibliographic record

VenueAsian Social Science · 2015
Typereview
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsnot available
Fundersnot available
KeywordsConflict managementCohesion (chemistry)Team effectivenessBusinessTeam compositionTeam managementPromotion (chess)Knowledge managementPsychologyProcess managementSociologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Conflict management mechanism and its optimization are increasingly reflected not only associated with the individual members of top management team, but also more closely related to the groups of top management team. The strength of cohesion of top management team decides the social resources and its centripetal force of family enterprises, so that the members could deal with team conflict with a flexible and effective way, and which will directly affect the decision quality and team performance of top management team of family enterprises. Based on the analysis of cohesion of top management team, conflict and its management mechanism, the study explores conflict management mechanisms of top management team of family enterprises, and analyzes the promotion strategies on cohesion of top management team on a review of conflict management.

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)0.012
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.190
GPT teacher head0.488
Teacher spread0.298 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2015
Admission routes1
Has abstractyes

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