Unlocking Profitability: A Panel Data Approach to Optimizing Working Capital in Nigerian Listed Companies
DOI:
https://doi.org/10.14738/abr.1302.18313Keywords:
Working capital, Profitability, accounts receivable and payable, Cash Conversion Cycle, Firm SizeAbstract
This study carried out a study on unlocking profitability: A panel data approach to optimizing working capital in Nigerian listed companies using data from 25 purposively sampled firms out of a population of 48. Employing Pooled OLS, fixed and random effects, and Panel GMM EGLS for analysis, the research unveils intricate relationships. The Random Effects Regression analysis reveals that Inventory Turnover (INV) has a statistically significant positive effect on Return on Assets (ROA) (p = 0.0249), highlighting the importance of efficient inventory management in enhancing profitability. Cash Conversion Cycle (CCC) also has a significant positive impact on ROA (p = 0.0052), reinforcing the need for effective cash flow management. Firm Size (SIZE) negatively affects profitability (p = 0.0359), suggesting that larger firms may face reduced efficiency. Accounts Receivable (ARC), Accounts Payable (AP), and Leverage (LEV) do not significantly influence ROA. The model explains 43.92% of ROA variability (R² = 0.4392). The Panel GMM EGLS results provide additional insights but show contrasting findings for INV, indicating complexity in the relationship. Coefficient Variance Decomposition highlights 'Size' and 'Account Receivable' as influential drivers of profitability. The study concludes that effective working capital strategies, especially in managing inventory turnover and optimizing cash conversion cycles, are crucial for improving financial performance in Nigerian manufacturing companies. Recommendations include emphasizing CCC, focusing on efficient inventory turnover, acknowledging the complexity of relationships, addressing endogeneity concerns, and recognizing the context-specific influence of firm size.
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Copyright (c) 2025 Fabian Terkura Hian, Criscent Ike Eya, Justin Terris Damsa

This work is licensed under a Creative Commons Attribution 4.0 International License.