¿CÓMO MEJORAR LA EXPANSIÓN INTERREGIONAL DE LAS MULTINACIONALES? EL CASO DE LAS FILIALES TRAMPOLÍN PARA LATINOAMÉRICA
Bibliographic record
Abstract
This article analyses a model of interregional expansion by using springboard subsidiaries. Being located in Spain, these units can facilitate the expansion of multinational companies in Latin America by providing part of the experiential knowledge required to succeed in the region, yet avoiding the initial requirement for investment. Based upon the expansion strategy of five European multinational firms, we develop an inductive model in which headquarters functions –coordination and knowledge creation processes - are distributed between the parent company and the springboard subsidiary along an accumulative process of capabilities. This model reflects the type and degree of commitment of both actors in each stage: whereas in the initial phase the springboard subsidiary and the headquarters act as substitutes, they execute complementary functions with the development of the local network in the target region. By demonstrating how a springboard subsidiary can help to align control to context, the model offers a tool for strategic analysis that helps avoid potential value destruction by parent companies.
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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 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".