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Record W4412049365 · doi:10.2139/ssrn.5340354

Single Family Offices as Firm Owners: Comparative Performance Effects

2025· preprint· en· W4412049365 on OpenAlexaff
Joern Block, Onur Eroglu, Dmitry Bazhutov, Danny Miller, André Betzer

Bibliographic record

VenueSSRN Electronic Journal · 2025
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicFamily Business Performance and Succession
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsBusinessIndustrial organization

Abstract

fetched live from OpenAlex

Single Family Offices (SFOs) have become an important vehicle for transgenerational wealth management. They address succession issues in family-owned firms, act as an investment vehicle for the business-owning family, and provide administrative services. Yet, we know little about the role of SFOs as firm owners, particularly how they influence the performance of the firms they own. Our study addresses this question and investigates the performance of SFO-owned firms. Arguing from an agency and monitoring perspective, we propose that SFO-owned firms will underperform firms directly owned by families. We further postulate that this underperformance will be mitigated when members of the owning family are involved in the management or supervisory board of the SFO-owned firm, and when the SFO-owned firm is publicly listed. Our results partially support these hypotheses and show that SFO-owned firms do indeed exhibit weaker financial performance than family-owned firms. This effect is diminished when a family member is directly involved in the management or supervisory board of the SFO-owned firm. Significant performance differences were not found between private versus listed SFO-owned firms. Our study contributes to the corporate governance and family business literatures on the performance effects of firm owners and blockholders. It also extends the nascent but growing literature on family offices. Practical implications are drawn for business owning families seeking to set up a family office as vehicles for succession and transgenerational wealth management.

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)0.004
metaresearch head score (Gemma)0.017
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 score0.021
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0210.001

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 head0.020
GPT teacher head0.255
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 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

Citations0
Published2025
Admission routes1
Has abstractno

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