Disentangling the corporate effect on subsidiary performance
Bibliographic record
Abstract
Abstract Research Summary Corporate parents are important to subsidiary performance, but prior strategy research presents mixed results about the extent to which parents drive subsidiary performance differences. Drawing on the corporate strategy literature, we argue that corporate parents’ influence depends on the size of the corporate portfolio that determines subsidiaries’ access to finite corporate resources and the contextual conditions—industrial relatedness and institutional distance—that favor or constrain the applicability of said resources. We find support using a variance decomposition analysis and data on 12,336 subsidiaries of 854 multinational firms. Our study demonstrates that the corporate effect varies according to the structure of the corporate portfolio and the subsidiaries in it. We reconcile theoretical arguments and empirical findings regarding the relative importance of corporate parents to subsidiary performance. Managerial Summary A core objective of corporate managers is understanding those channels most salient to subsidiary performance. The implicit assumption is that the corporate parent matters, but how much so remains unclear, especially since corporate parents cannot contribute equally to all subsidiaries. We demonstrate that the corporate parents of small subsidiary portfolios play a significant role in explaining subsidiary performance differences vis‐à‐vis parents of larger portfolios. We also show how this relative importance increases when subsidiaries exhibit higher industrial relatedness to and institutional distance from the parent. Our findings offer insights into the role of corporate parents in multiunit firms that operate across multiple industries and geographic locations, as well as the need to consider the heterogeneity of corporate influence within and between subsidiary portfolios.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.006 | 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".