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Record W3124179543

Strategic Divestments in Family Firms: Role of Family Structure and Community Culture

2005· article· en· W3124179543 on OpenAlexaff
Pramodita Sharma, S. Manikutty

Bibliographic record

VenueSSRN Electronic Journal · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsDivestmentBusinessOrganizational cultureDimension (graph theory)CollectivismIndustrial organizationMarketingPublic relationsMarket economyEconomicsPolitical scienceFinanceIndividualism
DOInot available

Abstract

fetched live from OpenAlex

Cycles of creative destruction and of regeneration are necessary for firm success.This examination seeks to understand this process as related to the divestment decision process within family firms.By looking at the influence of both family beliefs and community culture, the speed of a family firm's divestment decisions can be examined.Background information regarding divestment decisions is presented, as are the dimensions of culture that may influence these decisions.Although five dimensions of culture are often cited, this study only looks at the characteristics and influence of individual versus collectivist cultures. The structure of the family can also be quite influential when considering the speed of divestment decisions.Four family types are discussed, including the absolute nuclear family, the egalitarian nuclear family, the authoritarian nuclear family, and the community family.Also presented is the three-stage process from the business leader recognizing the need to divest to the sale and proceeding performance. Only the first two stages of the process are considered here (i.e., the need to divest and the ultimate sale of the business unit).Based on the cultural dimension of the study and the four family types that may be encountered, six propositions regarding the impact of culture and family type upon divestiture speed are proposed.Based on these propositions, several conclusions are made, but no empirical data is presented.The research and practice implications are also discussed. (AKP)

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.229
Teacher spread0.216 · 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 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

Citations6
Published2005
Admission routes1
Has abstractyes

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