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Record W3155843389 · doi:10.1093/icc/dtaa028

Business group persistence and institutional maturity: the role of management practices

2020· article· en· W3155843389 on OpenAlexaff
Zhixiang Liang, Michael Carney

Bibliographic record

VenueIndustrial and Corporate Change · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsConcordia University
Fundersnot available
KeywordsRestructuringMaturity (psychological)BusinessCorporate groupPersistence (discontinuity)Competitive advantageMarketingIndustrial organizationPolitical scienceFinanceCorporate governance

Abstract

fetched live from OpenAlex

Abstract A widely accepted account of business group (BG) functioning suggests that this common corporate form will dismantle and restructure with the progressive maturity of market-supporting institutions. However, even in mature institutional settings, BGs appear to persists and thrive. We hypothesize that BG persistence arises from an evolving competitive advantage because their competitive advantages with certain types of management practices do not decay with institutional development. We test our hypothesis with data assembled in the World Bank Enterprise Surveys (WBES). Empirical results show that several bundles of management practice differentiate BG affiliates and independent firms in the early phase of development but become less prominent at later stages. However, some of the differences in management practice bundles disappear, but others continue to differentiate independent firms and group affiliates in mature institutional jurisdictions.

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)0.005
metaresearch head score (Gemma)0.039
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 score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
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 head0.201
GPT teacher head0.222
Teacher spread0.021 · 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

Citations9
Published2020
Admission routes1
Has abstractyes

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