Semantic Scholar Open Access 2025

Structural Shifts in Machinery: Analysis of Fast-Growing Organizations

O. Dranko Aleksander Rezchikov

Abstrak

Structural shifts in the economy in the context of macroeconomic instability determine the promising profile of technologies and products. This paper considers a model for identifying and forecasting fast-growing organizations using the mechanical engineering industry as an example. The threshold of average annual revenue growth of 50% in current prices is used as a criterion for identifying fast-growing organizations. Big data analysis methods are used to identify fast-growing organizations within the segment under consideration. 1.8 thousand fast-growing organizations in the Russian industry with revenues exceeding $\mathbf{1 0 0}$ million rubles have been identified. An assessment of their growth using a sigmoid (logistic curve) shows a significant growth potential of $\mathbf{1 5 0 \%}$. The parameters of the logistic curve are identified using the least squares method. The data source is open data from the electronic Government of Russia, primarily from the Russian Federal Tax Service.

Penulis (2)

O

O. Dranko

A

Aleksander Rezchikov

Format Sitasi

Dranko, O., Rezchikov, A. (2025). Structural Shifts in Machinery: Analysis of Fast-Growing Organizations. https://doi.org/10.1109/ICCT67028.2025.11427839

Akses Cepat

Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Sumber Database
Semantic Scholar
DOI
10.1109/ICCT67028.2025.11427839
Akses
Open Access ✓