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Transformation of management strategies in railway transport under the global challenges of the modern economy

The relevance of the study is determined by the crisis of traditional methods of strategic management and forecasting in the Russian railway industry. The sector is facing unprecedented financial and managerial challenges amidst the global transformation of the transport business. The aim of the work is to analyze, from the perspective of strategic management, the global challenges to the development of railway transport (2025-2026), compare them with the current situation in Russia, and propose an author's concept for improving managerial approaches to forecasting to enhance the quality of strategic decisions in transport services. The methodological basis was a critical analysis of open scientific research, industry reviews, state statistics data, and expert publications. Results: three groups of global challenges for industry management were identified: the transition to hybrid energy models, the digitalization of management based on AI, and new operational concepts. A fundamental discrepancy was revealed between the global agenda and Russian realities, manifested in a systemic management crisis at Russian Railways (debt of about 4 trillion rubles, a drop in loading, and the failure of state forecasts with a deviation of up to 35 percentage points). Based on the analysis of modern methods of managerial forecasting (foresight methodology and machine learning methods), the hypothesis of a "managerial gap" forming between Russia and advanced countries is substantiated. The necessity of synthesizing qualitative and quantitative methods in the strategic planning of transport companies is proven. Scientific novelty lies in a systematic comparison of global managerial challenges and Russian structural problems, culminating in an original concept for integrating the foresight approach and machine learning methods for strategic decision-making under conditions of uncertainty. Practical significance: the results can be used to adjust the development strategies of transport companies, develop anti-crisis management programmers, and improve the activities of service sector enterprises integrated with transport flows.

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