Subsidiary‐level performance comparisons with external versus internal peers and subsidiary termination decisions: The role of host country experience
Bibliographic record
Abstract
Abstract Research Summary We examine how a subsidiary's host country experience affects the way in which multinational corporations' (MNCs) subsidiary termination decisions are geared toward subsidiary‐level social performance comparisons. For a subsidiary, social comparisons can be made against external peer subsidiaries (in the same industry and country but under different parents) and internal peer subsidiaries (in the same industry, country, and parent) whose performance levels constitute external social aspirations (ESA) and internal social aspirations (ISA), respectively. Using unpublished survey data on Japanese MNCs that offer subsidiary‐level performance data, we found that a subsidiary's below‐ESA performance is a stronger predictor of subsidiary termination than below‐ISA performance. However, as a subsidiary's host country experience increases, the effect of below‐ISA performance is amplified and even surpasses the effect of below‐ESA performance. Managerial Summary A subsidiary's performance relative to comparable peers serves as a critical criterion for MNC managers when evaluating the subsidiary's efficacy. However, little is known about how MNC managers' subsidiary termination decisions are geared toward subsidiary‐level performance comparisons against different reference groups and under what conditions these decisions vary. Using data on Japanese MNCs, we found that a subsidiary is at greater risk of termination when it underperforms relative to external peer subsidiaries (in the same industry and country but under different parents) than to internal peers (in the same industry, country, and parent). However, a subsidiary's host country experience amplifies MNC managers' sensitivity to underperformance relative to internal peers, while having less effect on their sensitivity to underperformance relative to external peers.
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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 | 0.002 | 0.010 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".