A bibliometric analysis on the role of corporate governance in micro, small and medium enterprises
Bibliographic record
Abstract
Purpose The purpose of this study is to analyse the existing research on the significance of corporate governance in micro, small and medium-sized enterprises (MSMEs) to identify significant contributors, emerging trends and prospective future research areas. Design/methodology/approach The authors perform a bibliometric analysis using a data set of 343 papers extracted from the Scopus database. R-studio software was used for performance analysis, while VOSviewer software was used for scientific mapping. Findings The study’s findings demonstrate that the research has attracted the attention of academics, which has led to a major rise in research over the previous two decades. “Corporate Ownership and Control” is the top contributing journal with the publication of 16 articles. The USA and UK are the top most productive countries. Simon Fraser University of Canada is the most contributing institution. Moreover, this study has identified four major themes: corporate governance assistance to small and medium enterprises, the role of corporate governance in society and management, family ownership and its importance in entrepreneurship, corporate governance issues, family firms and firm performance. Furthermore, the paper also defines the future research scope in each theme. Originality/value This study serves as a guide by mapping and analysing the intellectual structure of the corporate governance of MSMEs’ publications. Through this research, the authors better understand the academicians, managers, entrepreneurs and regulators about the condition of entrepreneurship and how they help businesses improve their performance. To the best of the authors’ knowledge, this is the first study to thoroughly analyse the literature on the role of corporate governance in MSMEs using bibliometrics.
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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 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.164 | 0.196 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| 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".