Effects of CEO Turnover and Board Composition Reform on Improvements in the Internal Control Quality
Bibliographic record
Abstract
Several serious accounting scandals have occurred in Japan in recent years (e.g., Olympus); however, the government, regulators, and auditing standard setters have struggled to identify new directions for corporate governance in listed companies, such as standard setting to address risks of fraud in an audit or the adoption of new corporate governance codes. The validity and effectiveness of monitoring by outside directors have received criticism within such a context. Nevertheless, in 2015, accounting fraud at Toshiba was discovered, which surprisingly involved upper management; the outside directors had failed to detect and prevent this fraud. Again, the monitoring function of the Japanese board of directors and outside directors was viewed with suspicion. Thus, this study examines Japanese corporations that disclose significant deficiencies (SDs) in internal controls over financial reporting (ICFR) and determines whether replacing the chief executive officer (CEO) and enhancing board members’ independence and financial expertise are followed by SD remediation. The results indicate that Japanese companies that disclose SDs in ICFR are more likely to replace their CEOs and enhance board independence. In addition, this study finds that although these actions do not affect SD remediation, upgrading the board’s accounting expertise does correlate positively with SD remediation. Moreover, if a company remediates a SD by increasing the number of accounting experts on the board, an increase in audit fees during the following term can be mitigated. These findings should be of interest to Japan’s regulators, auditing standard setters, and financial statement users when considering improvements in the quality of internal controls. In particular, these individuals must realize that the control environment is not improved in Japanese firms merely by replacing the CEO and increasing board independence, particularly because new CEOs encounter difficulties in changing the environment established by their predecessors.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".