Imperatives of Effective Working Capital Management and Profitability in the Banking Industry in Nigeria
Bibliographic record
Abstract
This study explored the imperatives of effective Working Capital Management (WCM) and Profitability in the banking industry in Nigeria. WCM core variables namely: Short-term Investments; Credits to customers and Account Receivables and Payables were used as proxy. Survey design was adopted and data were collected using questionnaires and analyzed with Pearson Product-Moment Correlation Coefficient (PPMCC) denoted by ‘r’. The findings to an extent counter apriori expectation. Though the values of ‘r’ exhibited positive signs affirming positive relationship, the strength of relationship is on the average. This was affirmed by the values of (r2), especially that of the variable ‘Credits to customers’ which stood low at 0.2229, meaning that the variable explained only 22.29% variation in Profitability. By implications, the results suggest that WCM variables have not yielded sufficient cash flows that could optimize profits. We therefore recommend efficient surveillance of WCM variables in order to reduce instances that lead to funds losses.
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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 | 0.005 |
| 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 | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".