The impact of digital information technology on improving the competitiveness of high-tech enterprises

Abstract

The article discusses the need to develop information technology in the context of digital transformation in order to increase the competitiveness of high-tech industries. It is determined that in connection with the rapid development of the digital economy, the adaptation of high-tech enterprises to new operating conditions, as well as increasing their competitiveness, is of particular relevance. The need to stimulate investment and entrepreneurial activity in the high-tech industry has been identified. The digital economy implies the automation of business processes within a high-tech enterprise, as well as in relations with contractors and government agencies through the use of modern information technologies. It is proved that the paramount task of the development of the digital economy in Russia is the implementation in the coming years of training the required number of IT specialists capable of providing a qualitative technological breakthrough. A special role in the digital economy is given to high-tech production. The competitiveness of high-tech enterprises is largely due to the use of modern digital technologies in management and production activities. In conditions of high-tech production, factors affecting the competitiveness of enterprises are unstable. A list of external and internal factors affecting the level of competitiveness of high-tech enterprises is established from the standpoint of the greatest degree of influence of information technologies on them. Ignoring the transition to a digital economy can even deprive a successful high-tech company of its competitive advantage. Creation of new and improvement of existing network information technologies in the digital economy and their implementation in domestic high-tech enterprises will increase the competitiveness of enterprises, and as a result, the country's competitiveness.

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“…The other is to count the frequency of words appearing in the document, which allows the algorithm to use more information and achieve a higher classification accuracy than the first definition. After calculating the word frequency matrix, weights are assigned to the vectors in the document according to the formula TFIDF [ 19 , 20 ]. where N is the number of documents, tf ik refers to the frequency of the k -th word in the i -th document, and df k refers to the number of documents that contain the k -th word in the entire training set.…”

“…e other is to count the frequency of words appearing in the document, which allows the algorithm to use more information and achieve a higher classification accuracy than the first definition. After calculating the word frequency matrix, weights are assigned to the vectors in the document according to the formula TFIDF [19,20].…”

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