Corporate Governance, Managerial Diversion, and Indonesian State-Owned Enterprises: A Literature Review
Bibliographic record
Abstract
This paper looks at managerial diversion and agency theory and how both arguments may be applied to describe the governance practices and performance of state-owned enterprise companies in Indonesia. Managers are the main focus of the approaches, on the assumption that managers tend to expropriate the firms' and shareholders' value for their own benefit instead of looking for ways to maximize shareholders' value and fulfill their stakeholders' needs. Indonesia is selected because it has the highest number of State-Owned Enterprise (SOE) companies among the ASEAN countries. The government holds more than 51 percent of the shares and has a unique governance structure with two-tier boards to manage and run the companies. Besides, most of Indonesia’s SOE companies have a tight connection with Indonesia’s political party. With these characteristics, the agency problem in Indonesia's SOE companies is more prevalent compared to other listed SOE companies. The managerial diversion, which is linked to corruption, might be the principal critical factor that hinders SOE companies from performing well. Thus, even with the introduction of a good corporate governance score by the Indonesian government, which is imposed on SOE companies, it may not be able to improve the overall financial performance of SOEs as well as governance practice in the companies. This paper's objective is to review and examine prior literature on corporate governance and managerial diversion from the perspective of state-owned enterprise companies in Indonesia.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".