A Global Mindset — A Prerequisite for Successful Internationalization?
Bibliographic record
Abstract
Abstract This study offers a contribution to our understanding of the role of a global mindset in the successful internationalization of small and medium‐sized companies. The particular focus is on the drivers of the global mindset and the connection with performance. We created a framework and tested it, empirically, with a representative sample of small Finnish companies in the field of information and communications technology (ICT). The findings indicate that managerial experience and market characteristics are important drivers of the global mindset, which, in turn, is one of the key parameters of international performance. The paper includes our conclusions, a discussion of the limitations of the study and the managerial implications, and suggestions for future research. Résumé La présente étude se propose de faire comprendre le rôle que joue la mentalité globale dans l'internationalisation heureuse des petites et moyennes entreprises. Nous nous appesantissons surtout sur les facteurs motivants de la mentalité et sur ses rapports avec la performance. Nous créons un cadre que nous testons, de façon empirique, à partir d'un échantillon représentatif de petites entreprises finnoises opérant dans le secteur des Technologies de l'information et de la communication (ICT). Les résultats indiquent que l'expérience en matière de gestion et les caractéristiques du marché sont des catalyseurs importants de la mentalité globale qui, à son tour, est l'un des paramètres clé de la performance internationale. L'étude dégage également nos conclusions, ses implications en matière de gestion, ses limites et propose des pistes de recherche futures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".