Global expansion and executive promotion of state‐owned enterprises
Bibliographic record
Abstract
Abstract Research Summary Executives in state‐owned enterprises (SOEs) are promoted differently from those in private firms due to the broader objectives of SOEs, which include non‐economic considerations. Research on SOEs often attributes executive promotions to firms' economic performance, without sufficient attention to the role of political performance. We find that executives of SOEs aligned with a government's globalization mandate, especially those investing in countries with political affinity, are more likely to be promoted as these investments further the government's political objectives and enhance executives' legitimacy with the bureaucratic system. The study broadens the literature on executive compensation by arguing that political alignment with government objectives matters. It also enriches institutional theory by suggesting a state‐firm‐executive legitimacy transmission. Managerial Summary When executives of SOEs align with a government's globalization goals and focus their investments in specific industries and countries, they often find more significant opportunities for career growth. Our detailed analysis, centered on SOEs directly overseen by the Chinese central government, supports our findings. This research offers valuable insights for the global strategy of SOEs. It suggests that while these investments can enhance the chances of advancing SOE executives who align with the state's political vision, promoting them based solely on political alignment, without considering long‐term project performance, may lead to challenges, underscoring the need for a balanced approach.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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".