CASH CONVERSION CYCLE AND FINANCIAL PERFORMANCE OF QUOTED INDUSTRIAL GOODS FIRMS IN NIGERIA
Keywords:
Cash Conversion Cycle, Financial Performance, Days Inventory Outstanding, Days Sales Outstanding, Days Payable OutstandingAbstract
The study ascertained the effect of Cash Conversion Cycle on financial performance of quoted Industrial Goods firms in Nigeria. The specific objective was to evaluate the effect of Days Inventory Outstanding, Days Sales Outstanding and Days Payable Outstanding on net asset per share of quoted Industrial Goods firms in Nigeria. Ex-post facto research design was adopted in the study. Thirteen listed industrial goods firms made up the population of the study while purposive sampling was used to select the sample size of nine firms. Secondary data were sourced from the firms’ annual reports over a thirteen year period from 2012-2024. Descriptive tools were used to analyse the data. Pearson correlation was used to assess the relationship between the variables. Test of hypotheses was conducted using panel least square regression. The study found the following: Days Inventory Outstanding has a negative and significant effect on Net Asset Per Share of quoted Industrial Goods firms in Nigeria (β = -0.015358, p = 0.0000); Days Sales Outstanding has a positive and significant effect on Net Asset Per Share of quoted Industrial Goods firms in Nigeria (β = 0.043945, p = 0.0000); Days Payable Outstanding has a positive and significant effect on Net Asset Per Share of quoted Industrial Goods firms in Nigeria (β = 0.012739, p = 0.0000). In conclusion, working capital dynamics within the Nigerian industrial goods sector are uniquely structured in a way that accommodates longer receivables and payables periods without adverse effects on firm value, while delays in inventory turnover are penalized in terms of financial performance. The study recommends that operations and supply chain managers adopt more responsive inventory management strategies, such as Just-in-Time (JIT) systems, lean inventory methods, or demand-driven restocking models.
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