Non-state Shareholders Board Power, Board Deep-level Faultlines and Acquisition Decisions by State-owned Enterprises in China
Bibliographic record
Abstract
In the context of mixed-ownership reform being further deepened in Chinese state-owned enterprises, based on principal-agent theory and resource-based theory, the study uses Chinese A-share listed state-owned enterprises from 2008-2019 as the research sample, and analysed the impact of non-state shareholders board power on acquisition decisions, in addition to exploring the moderating role of board deep-level faultlines. It was found that empowering non-state shareholders board power increased the likelihood of state-owned enterprises making acquisition decisions; However, if there were deep-level faultlines in the board, the ability of non-state shareholders board power to motivate state-owned enterprises to make acquisition decisions was diminished. The findings of this study suggest that giving non-state shareholders board power may bring benefits to state-owned enterprises in terms of business investment, but with a focus on a reasonable allocation of board members.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".