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Record W1823765967 · doi:10.1111/joms.12076

When do Non‐Family<scp>CEO</scp>s Outperform in Family Firms? Agency and Behavioural Agency Perspectives

2013· article· en· W1823765967 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Management Studies · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsUniversity of AlbertaHEC Montréal
FundersSocial Sciences and Humanities Research Council of CanadaUniversità Bocconi
KeywordsSocioemotional selectivity theoryAgency (philosophy)Corporate governancePrincipal–agent problemPower (physics)BusinessAgency costFamily businessPublic relationsMarketingPsychologyPolitical scienceSociologyFinanceShareholderDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract Family firms represent a globally dominant form of organization, yet they confront a steep challenge of finding and managing competent leaders. Sometimes, these leaders cannot be found within the owning family. To date we know little about the governance contexts under which non‐family leaders thrive or founder. Guided by concepts from agency theory and behavioural agency theory, we examine the conditions of ownership and leadership that promote superior performance among non‐family CEO s of family firms. Our analysis of 893 Italian family firms demonstrates that these leaders outperform when they are monitored by multiple major family owners as opposed to a single owner; they also outperform when they are not required to share power with co‐ CEO s who are family members, and who may be motivated by parochial family socioemotional priorities.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0000.001
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 head0.033
GPT teacher head0.258
Teacher spread0.225 · 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