Subject. Strategic planning at the regional level using data mining. Objectives. Development and substantiation of a methodology for optimizing the processes of strategic planning of socioeconomic development of regions based on the integration of data mining tools into the management cycle of the regional level. Methods. The research is based on systems and interdisciplinary approaches that combine the provisions of regional economics, the theory of strategic management and economic analysis. Methods of comparative and structural analyses, economic and mathematical modeling, predictive analytics, as well as data mining tools, including clustering algorithms, regression analysis, ensemble machine learning methods, and neural network models were used. Results. An adaptive model of strategic planning is proposed, in which data mining is considered as a system-forming element of the management process. Using the example of a subject of the Russian Federation, the possibilities of identifying hidden nonlinear relationships between socioeconomic indicators, improving the accuracy of forecasting key indicators and optimizing the allocation of investment resources are demonstrated. The results obtained indicate the significant superiority of analytical models based on data mining in comparison with traditional expert statistical approaches. Conclusions. The introduction of data mining into regional strategic planning processes ensures the transition from static and reactive management models to dynamic and proactive systems.
Keywords: strategic planning, data mining, regional economy, management digitalization
References:
Nizamutdinov M.M., Oreshnikov V.V., Davletova Z.A. [Development and testing of the toolkit of strategic planning of territorial development on the basis of an intelligent adaptive simulation model]. Biznes-informatika, 2024, vol. 18, no. 4, pp. 25–45. (In Russ.) DOI: 10.17323/2587-814X.2024.4.25.45 EDN: DWTFQM
Khomyakova A.A., Mizgirev L.S., Shergin V.V. [Using intellectual data analysis methods in management investment attractiveness of the region]. Izvestiya vysshikh uchebnykh zavedenii. Seriya: Ekonomika, finansy i upravlenie proizvodstvom, 2020, no. 2, pp. 14–23. (In Russ.) EDN: VPNKTP
Terekhin N.S., Rasulov G.A. [Data mining in strategic decision-making – opportunities for high-quality development of Russian enterprises]. Vestnik nauki, 2025, vol. 3, no. 3, pp. 613–619. (In Russ.) EDN: NBIGDQ
Klevtsova O.Yu., Ignat'ev S.A., Plotnikov V.A. [Improving public administration based on data mining technologies]. Izvestiya Sankt-Peterburgskogo gosudarstvennogo ekonomicheskogo universiteta, 2025, no. 2, pp. 50–58. (In Russ.) EDN: HYUYAF
Zemtsov S.P. [Potential for creation and implementation of artificial intelligence in the Russian regions]. Regional'nye issledovaniya, 2024, no. 1, pp. 34–47. (In Russ.) DOI: 10.5922/1994-5280-2024-1-3 EDN: RGTGVW
Bittiev M.Kh., Mayantsev V.S., Murzin S.A. [The impact of the introduction of artificial intelligence on the economy of companies]. Progressivnaya ekonomika, 2025, no. 5, pp. 106–116. (In Russ.) DOI: 10.54861/27131211_2025_5_106 EDN: HSJOAR
Konopleva Yu.A., Pakova O.N., Grigoryan R.Yu. [Artificial intelligence: development in Russia and main beneficiaries]. Vestnik Severo-Kavkazskogo federal'nogo universiteta, 2024, no. 3, pp. 91–99. (In Russ.) DOI: 10.37493/2307-907X.2024.3.10 EDN: TOXTTJ
Malkina M.Yu., Sochkov A.L., Kapustina Yu.I. [Forecasting regional GRP using artificial intelligence methods]. Journal of New Economy, 2025, vol. 26, no. 3, pp. 67–85. (In Russ.) DOI: 10.29141/2658-5081-2025-26-3-4 EDN: NWHFVD
Sazonova A.S., Kuz'menko A.A., Filippova L.B., Kurdin A.A. [Using data mining methods to forecast trends]. Izvestiya Tul'skogo gosudarstvennogo universiteta. Tekhnicheskie nauki, 2024, no. 10, pp. 316–319. (In Russ.) DOI: 10.24412/2071-6168-2024-10-316-317 EDN: AXNQOV
Izotova G.S., Eremin S.G., Galkin A.I. [Optimization of strategic planning processes in the system of state and municipal administration of the Russian Federation]. Nalogi. Pravo, 2025, vol. 18, no. 1, pp. 87–94. (In Russ.) DOI: 10.26794/1999-849X-2025-18-1-87-94 EDN: DDTRQD
Gnedkova M.A. [Improving strategic planning of digital transformation in the sphere of transportation and logistics in the constituent entities of the Russian Federation]. Vestnik Povolzhskogo instituta upravleniya, 2024, vol. 24, no. 4, pp. 4–13. (In Russ.) DOI: 10.22394/1682-2358-2024-4-4-13 EDN: CYHTBX
Shpakova R.N., Gorodetskii D.I. [Prospects of using artificial intelligence technologies to solve regional strategic planning problems]. Gosudarstvennoe upravlenie. Elektronnyi vestnik, 2025, no. 112, pp. 93–107. (In Russ.) DOI: 10.55959/MSU2070-1381-112-2025-93-107 EDN: YWTILH
