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Record W2130960096 · doi:10.1108/17439131311298511

Does family ownership create or destroy value? Evidence from Canada

2013· article· en· W2130960096 on OpenAlexaffabout
Kuntara Pukthuanthong, Thomas Walker, Dolruedee Thiengtham, Heng Du

Bibliographic record

VenueInternational Journal of Managerial Finance · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsConcordia University
Fundersnot available
KeywordsEnterprise valueShareholderStock exchangeAgency costBusinessValue (mathematics)Sample (material)Valuation (finance)Principal–agent problemMarket value addedAccountingAgency (philosophy)Stock (firearms)Market valueEconomicsFinanceCorporate governance

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to examine whether and how family ownership enhances or damages firm value. Design/methodology/approach – The paper studies a sample of Canadian companies listed on the Toronto Stock Exchange (TSX) between 1999 and 2007 and apply multivariate regression with firm value as a dependent variable. The paper measures firm value as Tobin ' s Q and ROA based either on net income or EBITDA. The independent variables include family firm dummy and ownership percentage. Findings – It is found that control-enhancing mechanisms which are often employed by family companies add value to companies. Furthermore, it is found that agency conflicts between ownership and management are less costly than those between majority and minority shareholders, suggesting that family ownership helps resolve the agency conflicts between ownership and management and in turn enhances firm value. Finally, it is found that family companies with founders as CEOs outperform those with descendants as CEOs. Research limitations/implications – The paper studies Canadian family firms; as such, the sample size is not relatively large. Nonetheless, the results should be generalized as Canada is one of the largest markets in the world and have high integration with the rest of the world. Practical implications – The results suggest investors should invest in family ownership firms. Originality/value – The paper shows whether firm ownership increases firm value and the determinant of family firm value.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.939

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 communication0.0000.003
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 head0.024
GPT teacher head0.223
Teacher spread0.199 · 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

Citations41
Published2013
Admission routes2
Has abstractyes

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