Analysis of clusters of Russian companies by level of development of digital transformation

Vollständiger Abstract

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Subject. Digital transformation of Russian public companies as a multilevel and heterogeneous process, including the introduction of artificial intelligence, big data, cloud computing, blockchain and applied digital technologies, as well as its reflection in corporate reporting. Objectives. Identification of empirical types (clusters) of digital transformation of Russian public companies based on a text analysis of annual reports for 2014–2024. Methods. The method of text analysis is used to measure the intensity of digital transformation. The k-means method with preliminary standardization of features was used to identify clusters. Results. In 2014–2024, the average aggregated digital transformation index in the sample increased 3.5 times (from 0.44 to 1.55), and the share of companies mentioning at least one digital technology increased from 28.6 to 56.7%. The category of "artificial intelligence" grew most dynamically (from 0.8 to 38.7% of companies), while mentions of cloud computing and blockchain peaked in 2018–2020 and then declined. Industry analysis has shown that telecommunications and the IT sector are the leaders in the intensity of digital transformation, while mechanical engineering, healthcare and chemistry demonstrate minimal values. The k-means method identifies four stable clusters of companies. Conclusions. The digital transformation of Russian public companies in 2014–2024 developed steadily and unevenly: against the background of the general growth of digital activity, high polarization remains between leading companies and the majority of low-involvement enterprises.