НЕЙРОСЕТЕВЫЕ МОДЕЛИ ОЦЕНКИ ВЛИЯНИЯ ЦИФРОВЫХ ТЕХНОЛОГИЙ НА ФИНАНСОВУЮ УСТОЙЧИВОСТЬ КОМПАНИИ

Abstract

The article is devoted to the development of a methodology for assessing the impact of digital technologies on the financial performance of a company. The digitalization of business processes of companies and organizations today is one of the main trends that ensure innovative development and competitiveness. Due to the diversity of companies in size, spheres of activity, operating conditions, the means and methods of digitalization can vary significantly. The introduction of certain technologies does not necessarily guarantee the success and financial stability of a company. Therefore, assessing the impact of digital technologies in making management decisions related to the implementation of innovations is an urgent task. The complexity of such an assessment is associated with the presence of a large number of factors affecting the economic performance of companies, while many factors cannot be quantified and can only be assessed in the form of expert qualitative assessments. The study was carried out on a statistical sample containing information on the level of business digitalization and the number of bankruptcies in the constituent entities of the Russian Federation. The indicator of the number of bankruptcies is used in this work as a resultant indicator reflecting the financial stability of companies in the region as a whole. The most widespread and massive digital technologies were selected as influencing factors: broadband Internet, ERP systems, RFID tags, cloud services, electronic sales systems, as well as digitalization indices of the constituent entities of the Federation. In the course of the research, to determine the impact of digital technologies on the financial stability of the company, a software model of artificial neural networks (ANN) was developed in the R Studio environment. In the work, the type of neural network is selected and all the necessary settings are calculated. The experiments carried out allowed us to optimize the network parameters in order to ensure the best accuracy. The final results of the study confirmed the impact of digital technologies on the sustainability of companies.