The Resilient Family Firm: Stakeholder Outcomes and Institutional Effects
Bibliographic record
Abstract
Abstract Manuscript Type Empirical Research Question/Issue Our study seeks to explain the relationship between publicly listed family‐controlled firms (FCFs) and investor and employee outcomes before and during the global financial crisis. Theoretically, we develop hypotheses suggesting that FCF resilience is beneficial to both investor and employees. Employing a large firm‐level data set of 2,949 firms across 27 European countries, we test the hypotheses that FCFs' long‐term orientation makes them resilient to the effects of economic shocks. In addition, using hierarchical linear modeling we evaluate family firm investor and employee outcomes, and the moderating impact of legal institutions protecting minority investors and employees. Research Findings/Insights We find that FCFs financially outperform non‐FCFs during the financial crisis, beginning in 2007 and reaching its lowest point in 2009, but show no significant differences during the stable‐growth period between 2004 and 2006. We evaluate two employee outcomes: downsizing and wage decreases. We find that FCFs are less likely to downsize their workforce or cut wages in both pre‐crisis and crisis conditions. Based upon hypotheses founded in the comparative capitalisms logic, we find significant institutional effects that are contrary to our predictions. Our findings suggest that investors and employees of FCFs achieve more favorable outcomes for their interests when the rules pertaining to investor protection and their enforcement are poorly developed. Theoretical/Academic Implications We contribute to the emerging literature on the institution‐based view of comparative corporate governance by demonstrating that family‐controlled firms' stakeholder outcomes are contingent upon legal protection for employees and investors under contrasting economic circumstances. Practitioner/Policy Implications Family owners, employees and minority investors should consider both firm‐level and country‐level governance institutions when investing in different countries, especially in times of economic crisis as jurisdiction‐level institutions and firm ownership choices produce variable outcomes for different stakeholders in both crisis and non‐crisis conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".