S.V. Prokopchina1, L.S. Zvyagin2

1, 2 Financial University under the Government of the Russian Federation (Moscow, Russia)
1 svprokopchina@fa.ru, 2 lszvyagin@fa.ru

To determine the specifics of information flows of small and medium-sized enterprises (SMEs) and propose principles of their metrological justification and monitoring for structured and unstructured information of SMEs. The digital image model of the enterprise formed in this way provides an excellent tool for analysts and management staff in order to increase the efficiency of their activities.

To substantiate the choice of the regularizing Bayesian approach (RBP) and intelligent technologies based on it for modeling, assessing the state and development of SMEs in conditions of uncertainty and situational instability. To develop a conceptual framework, a measurement model and a digital image of a small and medium-sized business based on the methodology and technologies of the RBP.

A set of methodological principles for monitoring and managing the development of SMEs has been developed, which, unlike existing ones, allows for sustainable management of SMEs in the context of digital economic transformation, information uncertainty, and situational instability of the external environment.

The proposed model of the digital image of an enterprise can be expanded to include additional characteristics and applied not only to SMEs, but also to large organizations, as an effective tool for monitoring, evaluating and analyzing the state and development of decision-making, including at the strategic level. In fact, the developed model is a digital twin of an enterprise operating in real conditions, characterized by the uncertainty of incoming information, which can be taken into account by the proposed digital tool.

Prokopchina S.V., Zvyagin L.S. The use of Bayesian intelligent technologies to implement a systematic approach to measuring the effectiveness of small and medium-sized enterprises. Neurocomputers. 2025. V. 27. № 6. P. 57−68. DOI: 10.18127/j19997493-202506-06 (in Russian).

1. Priroda, faktory` i izmerenie uspeshnosti predpriyatij malogo i srednego biznesa v Rossii: monografiya / pod obshh. red. V.I. Barxatova, D.A. Pletnyova. M.: Pero. 2015. 302 s.
2. Boby`lev S.N. Indikatory` ustojchivogo razvitiya: regional`noe izmerenie. Posobie po regional`noj e`kologicheskoj politike. M.: Akropol`, CzE`PR. 2007. 60 s.
3. Zhukov R.A., Prokopchina S.V. Programmny`j kompleks «Infoanalitik 2.0». Svidetel`stvo o gosudarstvennoj registracii programmy` dlya E`VM № 2024617544 ot 03.04.2024.
4. Odinczov B.E. Informacionny`e sistemy` upravleniya e`ffektivnost`yu biznesa: Uchebnik i praktikum dlya vuzov. M.: Yurajt. 2022. 206 s.
5. Odinczov B.E. Sbalansirovanno-celevoe upravlenie razvitiem predpriyatiya: modeli i texnologii: Monografiya. M.: INFRA-M. 2017. 162 c.
6. Tarasova N.P., Kruchina E.B. Indeksy` i indikatory` ustojchivogo razvitiya / Mater. mezhdunar. konf. «Ustojchivoe razvitie: priroda – obshhestvo – chelovek». T. 1. M.: ZAO «Innovacionny`j e`kologicheskij fond». 2006. 236 s.
7. Prokopchina S.V. Intellektual`ny`e izmereniya na osnove regulyariziruyushhego bajesovskogo podxoda. M.: Izd. dom «Nauchnaya biblioteka». 2021.  499 s.
8. Zhukov R.A., Prokopchina S.V. Modelirovanie funkcionirovaniya socio-e`kologo-e`konomicheskix sistem na osnove mnogourovnevogo optimizacionnogo podxoda v usloviyax neopredelennosti. Otchet o NIR № 22-28-20061. Rossijskij nauchny`j fond, 2022.
9. Parximenko V.A., Savchik O.A., Vernyaxovskaya V.V. i dr. Cifrovaya transformaciya v marketingovoj deyatel`no-sti: ot avtomatizacii k algoritmicheskomu marketingu. Big Data and Advanced Analytics. 2020. № 6-1. S. 303.
10. Luk`yanecz A.A., Prokopchina S.V. Podderzhka prinyatiya reshenij v upravlenii e`nergosnabzhayushhimi organizaciyami na osnove regu­lyariziruyushhego bajesovskogo podxoda. Tomsk: Izd-vo Tomskij nekommercheskij fond razvitiya regional`noj e`nergetiki. 2006. 399 s.
11. Koroleva D.A. Primenenie texnologij bajesovskix intellektual`ny`x izmerenij v auditorskoj praktike. E`konomika i upravlenie. Problemy` i resheniya. T. 1(61). 2017. S. 101–105
12. Prokopchina S.V. Novy`j tip nejronny`x setej: bajesovskie izmeritel`ny`e nejronny`e seti (BIN) na osnove metodologii regulyarizi­ruyushhego bajesovskogo podxoda. Myagkie izmereniya i vy`chisleniya. 2020. T. 35. № 10. S. 17–24.
13. Prokopchina S.V. Sistemny`j podxod v usloviyax neopredelennosti. Ot sistemny`x izmerenij k sistemnomu sintezu. Myagkie izmereniya i vy`chisleniya. 2018. № 11 (12). S. 3–13.
14. Mari l., Giordany A. Towards a concept of property evaluation type. XIII Symposium of IMECO, June, 2010.
15. Mary L., Lazarotti V., Manzini R. Measurement in soft systems: epistemological framework a case study. Measure-ment. 2009. V. 42. P. 241–253.