MNE Headquarters Disaggregation: The Formation Antecedents of Regional Management Centers
Bibliographic record
Abstract
Abstract This research examines region‐bound headquarters disaggregation in multinational enterprises (MNEs). We link the formation of regional management centres – both dedicated regional headquarters (RHQs) and regional management mandates (RMMs) granted to operating subsidiaries – to the complexity argument underlying organizational information processing theory. We demonstrate how different dimensions of complexity associated with the number and dispersion of an MNE's subsidiary network in a focal region affect whether, and in which form, region‐bound headquarters disaggregation takes place. Additionally, we consider boundary conditions affecting RMC formation based on within‐region experience, global MNE footprint, and between‐region effects. Empirically, we utilize a large global dataset of Japanese MNE foreign investments between 1992 and 2014, which allows us to perform event history analyses.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| 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 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".