A Study on the Financial Health of Listed Real Estate Companies via Multicriteria Decision-Making Methods

Under the influence of the pandemic and economic slowdown, real estate companies are facing severe financial risk, which has become a focal point of widespread concern. This study constructs a financial health evaluation model for real estate development enterprises on the basis of the entropy-VIKOR algorithm. Using China as a case study, this research selects real estate companies listed on the Shanghai and Shenzhen Stock Exchanges before the end of 2016 as the sample for empirical analysis. Sensitivity and validity analyses were conducted using 2020 data to ensure the robustness of the financial health evaluation model. The study identifies accounts receivable turnover and the interest coverage ratio as key secondary indicators of financial health in real estate companies, whereas operational capacity and debt repayment ability are critical primary indicators. The model is insensitive to weight perturbations, suggesting that its evaluation results are valid and predictive. Additionally, the pandemic and changes in the macroeconomic environment have negatively impacted corporate financial conditions, but internal adjustments and optimization strategies have contributed to the recovery of financial health. Finally, we analyze the research findings and provide targeted recommendations, with the aim of enabling real estate enterprises to respond better to macroeconomic and policy changes, thereby enhancing their financial health and market competitiveness.