25 Years internationalization research in SMEs, a scientometric analysis
Bibliographic record
Abstract
Purpose The varying nature of the competitive environment of small- and medium-sized enterprises (SMEs), contributing significantly to gross domestic product in most countries, has made their moving toward internationalization and global competition unavoidable in such a way that the life cycle of research in this area is experiencing a period of rapid growth. This study aims to evaluate the status of research on SME internationalization based on bibliographic records retrieved from the Web of Science Core Collection and Scopus. Design/methodology/approach Using a scientometric analysis, reviewing the important points and the boundaries of research on SME internationalization as well as practicing co-occurrence and burst detection analysis. Findings Through a rigorous examination of the crucial points and boundaries within the realm of SMEs internationalization research, coupled with an analysis of co-occurrence and burst detection techniques to detect contemporary hotbed topics, this study has uncovered that the predominant focus of current discourse centers around the areas of networks and networking, as well as internationalization models and entry into the global arena. Moreover, it gives insight that future investigations will shift toward enhancing SME internationalization performance, while simultaneously prioritizing the expeditiousness of their entrance into international markets. The insights garnered from this inquiry are expected to facilitate salient contributions to future literature in this area, thereby advancing our understanding of these complex phenomena. Practical implications The trend of the research in this field can be useful for enthusiasts. In this context, the life cycle of research on SME internationalization has been drawn that shows the period of research growth of publications is almost between 2005 and 2023, and the saturation will be approximately from 2023 to 2035. The top researching SME internationalization in the world have been occurred in the USA, England, Canada, Sweden countries and in Department of Management, Department of Marketing, School of Management, Faculty of Management Studies institutions. Also, most of the research has been published in Journal of International Business Studies, International Business Review and Strategic Management Journal. Originality/value This study accordingly provided a valuable perspective for future research in this line.
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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 | 0.011 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.086 | 0.132 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".