Determinant Financial Distress: Evidence Manufacture Company in Indonesia Stock Exchange 2018 – 2022 - Ida Ayu Fatmayuni; Sri Dwi Ari Ambarwati; Hendro Widjanarko (Profesional Muda Cendekia Publishing, 2024)
Research Aims: This study aims to examine the impact of six financial ratios—profitability (ROA and ROE), liquidity ratio (CR and QR), solvency ratio (DAR and DER), activity ratio (TATO), sales growth (SG), and market value (EPS and MBV)—on the likelihood of financial distress in manufacturing companies. The research focuses on determining the relationships between these ratios and the binary variable indicating financial distress. Design/methodology/approach: Using purposive sampling, 147 manufacturing companies were selected based on specific criteria, with financial distress defined by negative equity or negative net income for two consecutive years. Logistic analysis was employed to analyze the data, and STATA17 software was used for statistical analysis. Research Findings: The study reveals that ROA, ROE, QR, and TATO have a significant negative effect on financial distress, while DAR and MBV show a significant positive effect. CR, DER, SG, and EPS, however, exhibit no significant relationship with financial distress. Approximately 33% of the manufacturing companies studied experienced financial distress. Theoretical Contribution/Originality: This research contributes by examining the specific impact of financial ratios on the likelihood of financial distress, providing insights into which ratios are significant predictors. The study offers a nuanced understanding of the financial health of manufacturing companies. Research limitation and implication: Limitations include the use of a specific binary variable for financial distress and the focus on manufacturing companies. Future research may explore diverse sectors and incorporate additional variables for a comprehensive analysis. The findings suggest that companies can monitor and manage specific financial ratios to mitigate the risk of financial distress. This insight can guide strategic financial planning and decision-making in the manufacturing sector.