The impact of corporate governance on firm competitiveness and performance of small and medium enterprises in South Africa: A case of small and medium enterprises in Vanderbijlpark
Bibliographic record
Abstract
Orientation: Corporate governance adoption and compliance are an issue augmenting in importance recently and have been extended to business enterprises of any size including small and medium enterprises (SMEs).Research purpose: This study seeks to examine the impact of corporate governance adoption on the firm competitiveness and performance of SMEs in Vanderbijlpark.Research design, approach and method: The study employs a cross-sectional research design, which employed quantitative methods. One hundred fifty-two SME owners or managers were selected from Vanderbijlpark in Gauteng, South Africa. The collected data were analysed using a structural equation modelling system by using Smart PLS software.Main findings: The principal findings of this study revealed that the implementation of corporate governance by SMEs significantly and positively affected their competitiveness and performance.Practical and managerial implications: The paper provided practical implications and made some recommendations.Contribution or value-added: This article bridges the gap between theory and practice because it has both an economic and commercial impact in practice. It can be used in influencing public policy, teaching and research (because it contributes to the body of knowledge, particularly regarding SME corporate governance in emerging markets). An important aspect of this article is that it gives a framework for additional similar studies in other locations within emerging markets to test the generalisability of the findings. For teaching purposes, it provides a template for how to assess the link that exists between corporate governance and SME performance. Lastly, the article gives a unique empirical analysis of the relationship that exists between corporate governance compliance and performance of firms in South Africa, and thereby giving a valid contribution to corporate governance literature.
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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 | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".