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Record W3015244304 · doi:10.1177/1042258720910950

Do Family Firms Have Higher or Lower Deal Valuations? A Contextual Analysis

2020· article· en· W3015244304 on OpenAlexafffund
Zulfiquer Ali Haider, Jialong Li, Yefeng Wang, Zhenyu Wu

Bibliographic record

VenueEntrepreneurship Theory and Practice · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsUniversity of Manitoba
FundersCanada Research Chairs
KeywordsSocioemotional selectivity theoryValuation (finance)DescendantCorporate governanceInternationalizationBusinessSample (material)Differential (mechanical device)AccountingInternational tradeFinancePsychology

Abstract

fetched live from OpenAlex

How does the socioemotional wealth (SEW) of a family firm affect its deal valuation in acquisition? Using a sample of 515 completed transactions of S&P 500 firms over the period 2003–2016, we examine a number of contexts and find that SEW creates differential valuations of targets by family firms vis-à-vis non-family firms. Particularly from an internationalization perspective, acquisitions may be an ideal option for family firms because foreign acquisitions may be loosely coupled from the core firm. Post-hoc analyses on the heterogeneity in family governance reveal that founder and descendant board chairs may have different perceptions of SEW.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.306
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.

Study designNot applicable
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

Citations30
Published2020
Admission routes2
Has abstractyes

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