Role of Business Management into the Success and Survival of Small Businesses: The Case of Star Learning Centre in Botswana
Bibliographic record
Abstract
The study aimed to establish the aspects of management, which have led to the survival, and success of the small-scale businesses in Botswana- a case of Star Learning Centre. The questions explored were 1) What is the role of management in the survival or success of Star Learning Centre? 2) What management styles, systems and practices are appropriate for Star Learning Centre and other small scale businesses in the Botswana? 3) What work culture is appropriate for business success? 4) What factors have enabled the Star Learning Centre to succeed? The study used a convenience sample comprising 31 staff members of Star Learning Centre. The probability sampling approach was applied because the number sampled was known. Questionnaires, observation and interview methods were used as the main instruments. Findings revealed that Star Learning Centre success can be attributed to effective management, team work, timely communication, conducive working environment. The problems/challenges faced by the Centre were: shortage of capital, shortage of land, lack of open discussion between staff and management, and an unsatisfactory remuneration system. The study recommends further research that may capture more and bigger businesses.
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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 | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".