Corporate Governance and Firm Performance: A Comparative Analysis between Listed Family and Non-Family Firms in Japan
Bibliographic record
Abstract
This study aims to explore the relationship between corporate governance and financial performance of publicly listed family and non-family firms in the Japanese manufacturing industry. The study obtains data from Bloomberg over the period 2014–2018 and covers 1412 firms comprising of 861 non-family and 551 family firms. Our results show that family firms outperform non-family counterparts in terms of return on assets (ROA) and Tobin’s Q when a univariate analysis is invoked. On multivariate analysis, family firms show superior performance to non-family firms with Tobin’s Q. However, family ownership negates firm performance when ROA is taken into account. Regarding the impact of governance elements on Tobin’s Q, institutional shareholding appears to be a significant and positive factor for promoting the performance of both family and non-family firms. Furthermore, board size encourages the performance of non-family firms, while such influence is not observed for family firms. In terms of ROA, foreign ownership inspires the performance of both family and non-family firms. Moreover, government ownership stimulates the performance of family firms, while board independence significantly negates the same. Besides, we find that the performance of family firms run by the founder’s descendants is superior to that of family firms run by the founder. These findings have critical policy implications for family firms in Japan.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".