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Internationalization of Family Firms

2020· book-chapter· en· W3111357791 on OpenAlexaff
Liena Kano, Alain Verbeke, Luciano Ciravegna

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCorporate governanceInternationalizationBounded rationalityDysfunctional familyIndustrial organizationBusinessInternalization theoryAffect (linguistics)MicroeconomicsEconomicsSociologyFinancePsychologyTransaction cost

Abstract

fetched live from OpenAlex

Abstract We infuse new internalization theory (NIT) with insights from family firm research, specifically, micro-foundational drivers of family managers’ decision-making such as socio-emotional wealth (SEW) preferences and bifurcation bias. We argue that the international governance of family firms is best explained through a model that combines efficiency-based logic (rooted in NIT) and affect-based logic (rooted in SEW). Such explanation expands the boundaries of NIT by addressing both international competitive success of family firms vis-à-vis their non-family counterparts and their divergence from efficient international governance and consequent failure in host markets. Disciplined pursuit of functional (as opposed to dysfunctional) aspects of SEW can facilitate the firm’s ability to economize on bounded rationality and reliability and create an environment conducive to value generation in host markets. However, unconstrained pursuit of SEW will lead to governance inefficiencies. Family firms can enhance the functional impact of SEW by implementing anticipative, large-scale strategies to economize on bifurcation bias. Ultimately, the main prediction of NIT holds—only efficient governance will be sustained in the long run.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.988
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
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 head0.032
GPT teacher head0.199
Teacher spread0.167 · 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
GenreOther

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

Citations1
Published2020
Admission routes1
Has abstractyes

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