General Manager Staffing and Performance in Transitional Economy Subsidiaries
Bibliographic record
Abstract
Drawing from institutional theory, we address the issues that headquarters of multinational corporations (MNCs) face when selecting local versus expatriate subsidiary general managers (GMs). Our analysis of 2,315 MNC subsidiaries in China shows that foreign direct investment (FDI) legitimacy is a reliable measure of institutional environment differences at the subnational level and that the commonly used country-level measures, including institutional distance and cultural distance, mask pertinent withincountry differences. MNCs that invest in Chinese provinces with lower FDI legitimacy use more local nationals as subsidiary GMs, compared to MNCs that invest in provinces with higher FDI legitimacy. In provinces with low FDI legitimacy, subsidiaries with local GMs perform relatively better than subsidiaries with expatriate GMs. This effect is particularly strong for wholly owned subsidiaries, as compared with joint ventures, and applies to all provinces except the most developed coastal regions. In provinces with higher levels of FDI legitimacy, these effects are reversed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".