Measuring corporate management in business maturity forecasting models

Abstract

Modern corporate theory interprets enterprise-wide risk management (ERM) as an agent between stakeholders and corporate governance. In accordance with the latest ERM framework, corporate risk management in business includes the methods and processes used by organizations to manage uncertainty and use the opportunities associated with achieving their goals. The aim of the study is to measure corporate management in business maturity forecasting models. The author predicted a company cluster based on signal to noise ratio. As the basic model, the author used the calculation method proposed by G. Taguchi to assess product quality as well as for the design and optimization of processes. The research method used for the study was empirical. The author obtained financial performance data relating to all 218 companies from the SPARK database. It was applied two-step cluster analysis to compare companies within the sample. Also, it was calculated the geometric mean for each quantitative variable to avoid the influence of temporary shocks and distortions. The results of a nonparametric test showed that the relationship between the signal-to-noise ratio (SNR) and ERM is significant. Thus, based on the results of the theoretical and empirical studies, we can argue that the measurement of ERM through the SNR is justified.