Working Capital Management and Financial Performance: Evidence from Nigeria’s Public Listed Manufacturing Companies
Bibliographic record
Abstract
Working capital management is important in corporate finance and considerably impacts organizational profitability. The study investigates how working capital management impacts the performance (specifically in the context of financials) of publicly traded manufacturing companies listed on the Nigeria Stock Exchange (NSE). Data collected for this study was analyzed using Statistical Package for Social Sciences (SPSS) based on the sample of 18 manufacturing companies for five years from 2013 to 2017. Working capital management is important for all organizations as it can considerably impact profitability and financial performance. The linear regression study revealed a notable positive correlation between the Account Payable Period and profitability. An escalation in the duration of accounts payable is associated with increased profitability. The second regression model conclusion indicates that a reduction in the duration (days) to collect sales from consumers is linked to a reduction in the profit since accounts receivable are negatively and insignificantly correlated with profitability. The third discovery in this study revealed an insignificant adverse relationship between the conversion period for inventory and profitability. Manufacturing companies need to turn their inventory into sales to increase profits promptly. This analysis revealed an insignificant inverse correlation between the conversion cycle for cash and profitability.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".