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The impact of intelligent decision support systems on the transformation of management practices

Authors:

P.A. Mikhnenko

Bauman University, Moscow, Russia

Abstract:

The active implementation of intelligent decision support systems (IDSSs) entails changes in management practices. The article aims to assess the systemic impact of technological, organizational, and human factors of IDSSs implementation on the transformation of management methods in Russian companies. The research methodology resides in a systems approach to management. Regression analysis was used as the research method. To verify the robustness of the results, the study relies on the method of sequential construction of four nested multiple linear regression models with the addition of control variables. The evidence base consisted of data from an online survey of 104 executives and employees of Russian companies, who are experienced in implementing or operating intelligent systems. The paper identifies statistically significant systemic relationships between the factors under consideration and the transformation of management practices. The organizational factor was proven to contribute the most to the management system’s transformation. The research results establish the robustness of the statistical relationships to the influence of the company size, industry, and regional specificity and empirically confirm the importance of a comprehensive approach to the digital transformation of management. The findings provide a basis for developing IDSSs implementation strategies. Prospects for further research involve conducting longitudinal analysis to clarify the cause-and-effect relationships between the use of these systems and the transformation of management methods.

Keywords: digital transformation; management; artificial intelligence; intelligent system; organizational change; regression analysis.

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For citation: Mikhnenko P.A. (2025). The impact of intelligent decision support systems on the transformation of management practices. Upravlenets / The Manager, vol. 16, no. 6, pp. 2–16. DOI: 10.29141/2218-5003-2025-16-6-1. EDN: IHXAKM.