Financial Distress Warning: An Evaluation System including Ecological Efficiency

This article established an evaluation system including ecological efficiency that can provide a more accurate financial distress warning for companies. Based on the data of listed companies, Data Envelopment Analysis (DEA) is applied to evaluating the business efficiency, financial efficiency, financing efficiency, human capital efficiency, and ecological efficiency, and the accuracy of the evaluation system that includes ecological efficiency is measured by artificial neural networks (ANNs). Besides, the logit model is applied to test the results. Our experiments indicate that participating in ecological efficiency improves the evaluation system of financial distress warnings, and its accuracy is much better than the traditional evaluation system in the long run. The logit model confirms the essential of ecological indicators in financial distress warning, and the behavior of observing environmental regulation will prevent enterprises from getting into financial distress. Finally, suggestions on improving green finance and promoting technological innovation are propounded, in which technological innovation (TI) is the core of an enterprise's competitiveness, and green finance can accelerate that process.

Automated summary

This article established an evaluation system that includes ecological efficiency to provide a more accurate financial distress warning for companies. By using Data Envelopment Analysis, artificial neural networks, and the logit model, the importance of ecological efficiency in financial distress warning is confirmed. Suggestions for improving green finance and promoting technological innovation are also proposed, emphasizing the core role of technological innovation in enhancing enterprise competitiveness and the acceleration provided by green finance.