Analysis of economic and mathematical modeling of industrial enterprise functioning at multicollinearity based on parameterization
Authors:
N. Lokhman, Dr. Sc. (Econ.), Assoc. Prof., orcid.org/0000-0002-0116-2525, Donetsk National University of Economics and Trade named after Mykhailo Tugan-Baranovsky, Kryvyi Rih, Ukraine
V. Serebrenikov, Cand. Sc. (Tech.), Assoc. Prof., orcid.org/0000-0002-5490-5601, Donetsk National University of Economics and Trade named after Mykhailo Tugan-Baranovsky, Kryvyi Rih, Ukraine
T. Beridze, Cand. Sc. (Tech.), Assoc. Prof., orcid.org/0000-0003-2509-3242, Kryvyiy Rih faculty of Zaporizhzhia National University, Kryvyi Rih, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
A. Cherep, Dr. Sc. (Econ.), Prof., orcid.org/0000-0001-5253-7481, Zaporizhzhia National University, Zaporizhzhia, Ukraine
I. Dashko, Cand. Sc. (Econ.), Assoc. Prof., orcid.org/0000-0001-5784-4237, Kryvyiy Rih faculty of Zaporizhzhia National University, Kryvyi Rih, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract:
Purpose. Investigation of multicollinearity in multifactorial economic and mathematical regression models of activity of Inhulets Mining and Processing Plant and reduction of its negative influence based on application of the parameterization method.
Methodology. To reduce the negative impact of multicollinearity in multifactorial regression models, a technique is developed that is based on the transition from the function of several variables to its parametric representation by analyzing the correlation matrix between factors in order to eliminate mutual correlation.
Findings. Economic and mathematical modeling of the activity of the JSC Inhulets Mining and Processing Combine showed that the presence of multicollinearity when applying a multifactor regression model leads to a distortion of the obtained results, which reduces the practical value of the model. The application of the parametrization method made it possible to reduce the influence of multicollinearity by providing parametric representations of the economic-mathematical model of holding the real economic process. The application of the parameterization method makes it easier to construct an economic-mathematical model in the form of regression equations, to reduce the negative impact of multicollinearity in the implementation and meaningful analysis of features of economic and mathematical modeling using multivariate regression equations.
Originality. For the first time, the application of the parameterization method is proposed, which allows us to simplify the construction of an economic-mathematical model in the form of regression equations. Using the parameterization method allows reducing the uncertainty in the synthesis of multivariate regression equations, ensuring appropriate adequacy.
Practical value. The analysis of the obtained results of economic and mathematical modeling of the activity of the Inhulets Mining and Processing Plant based on significant statistical material using the developed algorithm of elimination of multicollinearity confirmed the effectiveness of the proposed approach. It is recommended to include the developed algorithm for elimination of multicollinearity by parametrization in the practice of management of economic activity of mining enterprises.
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