Driving SMEs’ Performance in South Africa: Investigating the Role of Performance Appraisal Practices and Managerial Competencies
Bibliographic record
Abstract
Managerial competencies and performance appraisal practices are often ignored when considering the performance of Small-to-Medium Enterprises (SMEs). Yet, these competencies and practices are fundamental for the survival of the SMEs. SMEs are critical for economic growth and job creation in many economies. The current study sought to establish whether managerial competencies and performance appraisal practices correlate with SMEs’ performance in South Africa. Firm performance was measured using two variables: innovation and return on investment (ROI). The study adopted a structural equation modelling analytical approach. Interpersonal competencies were found to be a significant factor of managerial competencies, but conceptual and political competencies were not. The study also found that managerial competencies, and not performance appraisal practices, significantly correlated with both innovation and ROI. The study recommends that performance appraisal practices be tailored to suit SMEs in the developing countries context.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".