SPATIAL CONSISTENCY AND TEMPORAL PERSISTENCE IN MNEs’ REPETITIVE STRATEGIC RESOURCE ALLOCATIONS
Bibliographic record
Abstract
Although scholarship regarding dynamic capability has provided meaningful contributions to our understanding of the patterns of strategic decisions, less is known about their manifestations in the context of multinational enterprises (MNEs). By focusing on recursive, high-stake strategic resource allocation decisions, we disentangle the time and space dimensions of the deployment of capabilities. More specifically, we examine the stability patterns in MNEs and their subsidiaries as a result of the application of capabilities manifested as simple organizational rules. We develop two complementary core constructs for our purpose: temporal persistence and spatial consistency. Utilizing two primary dimensions of international strategy, namely expatriate assignment and equity ownership level decisions, respectively representing repetitive and quasi-repetitive decisions, we consider the role of degree of repetitiveness in the stability and dynamism of decisions and their influence on firm performance. We find a positive effect on performance for MNEs’ spatial consistency across subsidiaries for expatriation (as a repetitive decision), and a negative effect for spatial consistency in equity ownership (as a quasi-repetitive decision). We also observe for temporal persistence in expatriation, a positive effect on performance.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".