Algorithm for Selecting Enterprises with Stable Entrepreneurial Activity to Justify Institutional and Corporate Decisions

The article represents the author’s approach to substantiating the algorithm for selecting enterprises with stable entrepreneurial activity in the context of changing internal and external conditions of their functioning. The dynamics of the institutional conditions of activity and the life cycle of enterprises in a particular market depend on decisions made by the state, global trends associated with the processes of the fourth industrial revolution and other factors. The article notes that methods for assessing entrepreneurial activity were developed within the framework of a fairly young theory of business demography and currently, in combination with modern digital information processing technologies, contain significant analytical potential that can be used to remove uncertainty when adopting certain state institutional decisions. However, today there is no generally accepted approach to choosing a method in relation to the actual system of indicators for assessing the dynamics of the functioning of an enterprise in the market. The paper proposes a methodology for selecting enterprises with stable entrepreneurial activity, consisting of several successive stages: classification of enterprises according to business demographics; formation of a cluster of enterprises with the maximum life cycle period using basic statistical approaches; assessment of enterprises of the formed cluster in terms of revenue received using the Kendall coefficient of agreement; selection of enterprises with stable entrepreneurial activity according to the criterion of maximizing the Kendall coefficient of agreement. Practical testing of the proposed algorithm was carried out on the basis of the market of IT enterprises in the Rostov region operating under OKVED code 62.02 “Consulting activities and work in the field of computer technology”. As a result, a sample of 13 enterprises was formed, the assessment of which showed high consistency according to the Kendall coefficient of agreement (0.704). Testing using the Pearson criterion showed high statistical reliability of the result obtained. All this provides an opportunity for further analysis of those internal factors due to which it is possible for other enterprises to ensure an increase in the level of entrepreneurial activity in the market under study and thereby increase their level of competitiveness.

1. Belitskaya O.V. Demography of Russian business: Key problems and trends. Estestvennogumanitarnye issledovaniya=Natural-humanities studies, 2021, no.34(2), pp.26-30 (in Russian). DOI: 10.24412/2309-4788-2021-10944.

2. Vazhenin S.G., Vazhenina I.S. Features of transformation business demographies of enterprises in the modern economic space of Russia. Federalism’, 2023, vol.28, no.3(111), pp.72-87 (in Russian). DOI: 10.21686/2073-1051-2023-3-72-87.

3. Kochetygova O.V., Inozemcev E.S., Golovko M.V. Analysis of the business demography of organizations in the Russian Federation for 2012–2020. Vestnik IEAU, 2021, no.31, pp.1-8 (in Russian).

4. Lebedeva A.B., Bakirova R.R. Analiz dinamiki smertnosti i rozhdaemosti predpriyatij [Analysis of the dynamics of mortality and birth rates of enterprises]. Modern Science, 2021, no.7, pp.50-53.

5. Mezenceva E.V., Korolyuk E.V. Business demography as an indicator of the effectiveness of socioeconomic development of the region. Upravlencheskij uchet=Management Accounting, 2022, no.2-1, pp.125-130 (in Russian). DOI: 10.25806/uu2-12022125-130.

6. Polozhenceva Yu.S., Androsova I.V. Prospects for the development of business demography of economic entities. CITISE, 2019, no.4(21), pp.136-145 (in Russian). DOI: 10.15350/24097616.2019.4.15.

7. Poluyanov V. Selecting a leader enterprise using a dynamic competitiveness assessment model. Sovremennaya konkurentsiya=Journal of Modern Competition, 2023, vol.17, no.5, pp.73-82 (in Russian). DOI: 10.37791/2687-0657-2023-17-5-73-82.

8. Poluyanov V.P. Ranking of universities in the Rostov region by the criterion of the efficiency of their functioning. Nauka i obshchestvo – 2021: Materialy mezhdunarodnoi nauchnoi konferentsii (Rostovna-Donu, 9 aprelya 2021 g.) [Science and Society – 2021: Proceedings of the International Scientific Conference (Rostov-on-Don, April 9, 2021)]. Ed. by N.B. Osipyan, I.V. Makarova, M.I. Zhbannikova. Moscow, Moskovskij universitet im. S. Yu. Vitte, 2021, pp.244-249 (in Russian).

9. Poluyanov V.P., Borisov N.A. Rezul’taty sravnitel’nogo analiza instrumentov dlya upravleniya ITproduktami na rynke programmnyh sredstv [Results of a comparative analysis of tools for managing IT products on the software market]. Informacionnye sistemy, ekonomika i upravlenie: Uchenye zapiski [ Information Systems, Economics and Management: Scientific Notes]. Rostov-on-Don, Rostov State Economic University (RINH), 2023, pp.168-174.

10. Poluyanov V.P., Poluyanov E.V. Institutional characteristics of the market of computer technologies and consultative activities of the Rostov region. Innovacionnye tekhnologii v mashinostroenii, obrazovanii i ekonomike, 2021, vol.30, no.1(19), pp.13-19 (in Russian).

11. Poluyanov V.P., Poluyanov E.V. Ranking of districts of the Rostov region by housing and utilities quality indicator. Regional’nye problemy preobrazovaniya ekonomiki, 2019, no.11(109), pp.122-137 (in Russian). DOI: 10.26726/1812-7096-2019-11-122-137.

12. Poluyanov V.P., Poluyanova E.I. Ranking of university branches by the criterion of the efficiency of their functioning (on the example of the Rostov region). Innovacionnye tekhnologii v mashinostroenii, obrazovanii i ekonomike, 2021, vol.30, no.1(19), pp.20-25 (in Russian).

13. Poluyanov V.P., Stepanenko K.V. Dinamika otdel’nyh pokazatelej funkcionirovaniya predpriyatij IT otrasli Rostovskoj oblasti [Dynamics of individual performance indicators of IT industry enterprises in the Rostov region]. Doneckie chteniya 2023: Obrazovanie, nauka, innovacii, kul’tura i vyzovy sovremennosti: Materialy VIII Mezhdunarodnoj nauchnoj konferencii (Doneck, 25–27 oktyabrya 2023 g.) [Donetsk Readings 2023: Education, Science, Innovation, Culture and Challenges of Our Time: Proceedings of the VIII International Scientific Conference (Donetsk, October 25–27, 2023)]. Donetsk, Doneckij gosudarstvennyj universitet, 2023, pp.349-352.

14. Somov V.L., Tolmachev M.N. Trends of main indicators of business demography. Voprosy statistiki, 2020, vol.27, no.5, pp.58-64 (in Russian). DOI: 10.34023/2313-6383-2020-27-5-58-64.