Extending Uppsala Model with Springboard Perspective in Emerging Multinational’s Sequential Internationalisation—Evidence from a Construction Company’s Expansion in Africa
Bibliographic record
Abstract
The Uppsala model explains the traditional internationalisation process of multinational enterprises (MNEs), which gradually begin to internationalise from countries with smaller psychic distances. However, in the turbulent global economy, an increasing number of MNEs from emerging markets (EMNEs) adopts a more radical and aggressive approach, strategically using international expansion as a springboard to enter an overseas market and radiate surrounding countries and regions. By combining the springboard perspective and the Uppsala model, we analyse a series of processes from EMNE’s first entry into an overseas market to the successful localisation and expansion of international business. This radical model of international expansion has not been thoroughly studied. This empirical study aims to address this research gap by using a qualitative method and an in-depth case study. This paper conducted a semi-structured interview with 16 expatriates, executives, and middle-level managers from the case company in 2016. As one of the few single case studies that systematically studies the internationalisation process of EMNEs and provides first-hand empirical evidence, it contributes to practice and provides a contextual reference for EMNEs.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".