An Analysis of the Financial Performance of Selected Savings and Credit Co-Operative Societies in Botswana
Bibliographic record
Abstract
The co-operative sector plays an important role in a country’s socio-economic development. This paper evaluated the financial performance of 9 selected Savings and Credit Co-operative Societies (SACCOSs) in Botswana by analysing audited financial statements of a five-year period from 2008 to 2012. The analytical techniques used include descriptive statistics of financial aggregates and ratios, correlation, regression and common size analyses. The financial aggregates analysed included all items that impact income generation as well as items that represent the financial position of the selected societies. The findings underscored that the selected SACCOSs achieved good financial results and were in strong financial position. The results also indicated a significant relationship between Net Profit ratio and Capital Employed Ratio to inform that the Net Profit Ratio was the most important explainer of Return on Capital Employed. The 5 year common size analysis also revealed a growth in income and in the financial status of the selected societies. The capital structure of these societies was characterised by substantial share of internal funds. Conclusively, maintaining an optimal balance between the interest on loans and interest on members’ savings, and investing extra cash in diversified portfolio to reduce the risk levels would make the SACCOSs grow and function more productively and profitably. They would also then succeed in attracting more members and thereby significantly contribute towards poverty reduction and economic diversification drives in the country.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".