Building world-class enterprises though mixed-ownership reform: explaining performance differences in minority and majority state-owned enterprises
Why this work is in the frame
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Bibliographic record
Abstract
Purpose In the context of China’s efforts to build world-class enterprises through mixed-ownership reform, this study aims to build an agency theory framework to analyze the differential relation between ownership structure and firm performance in majority versus minority state-owned enterprises (SOEs). It also evaluates the differential influence that political connectedness has on firm performance in the two types of SOEs. Design/methodology/approach Using a panel data set of Chinese state-controlled mixed-ownership enterprises covering the period 2010–2019, this paper uses ordinary least squares, random-effects, fixed-effects and three stage least squares regression analysis to study the differential impact of ownership structure and political connectedness on firm performance in majority versus minority SOEs. Findings In minority SOEs, firm performance is positively related to the ownership share of the largest private shareholder and state ownership positively moderates this relation. Furthermore, minority SOEs with a politically connected chairman perform worse than those with a politically connected chairman. In majority SOEs, there is no relation between the ownership share of the largest private shareholder and firm performance. In addition, majority SOEs with a politically connected chairman perform similar to those without a politically connected chairman. Originality/value The theoretical framework demonstrates that agency problems are substantially different in minority versus majority SOEs and that this influences how changes in ownership structure and in the type of chairman that is assigned affect firm performance. The empirical analysis confirms these predictions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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 it