Tools for Correlation and Regression Analyses in Estimating a Functional Relationship of Digitalization Factors

Digitalization processes affect all levels and spheres of human activities, from personal communications to public events. The widespread implementation of digital technologies has an ambiguous effect on the personal, social, and economic paths of modern society’s development. At the moment, there is no single approach to the estimation of digitalization’s impact, particularly on the financial and economic properties of a company. The objective of this study was to create multiple models for the assessment of digitalization’s impact on company performance. To accomplish this objective, the following steps were performed: conducting a literature survey on the experience with digital technologies’ implementation; selecting the most appropriate mathematical tools for correlation and regression analyses; determining a functional relationship between the factors and consequences of digitalization in terms of companies’ performance; identifying digitalization factors, risks, and their impact on the financial sustainability of companies; and creating a multiple regression model of the functional relationship between digitalization factors and the financial sustainability of companies. In the course of the study, a correlation analysis of the dependence of companies’ financial sustainability on a number of digitalization factors has been conducted, and different ways of using company performance data as effective features and predictive factors are offered. The article includes sampling data on the parameterization and quality evaluation of multiple regression models. The validity of the multiple models suggested was tested with actual statistical data obtained from 16 Russian companies. The application of the multiple regression model was devised to estimate digitalization’s impact on companies’ performance, and their financial sustainability can be seen as the most important practical implication of this study.