RISK-ORIENTED BUSINESS MANAGEMENT IN THE CONTEXT OF MARTIAL LAW

Abstract

Introduction. The functioning of enterprises in Ukraine under martial law is characterised by a high level of economic, financial and security uncertainty caused by full-scale military aggression, the consequences of the COVID-19 pandemic, disruptions of supply chains and increased geopolitical risks. Under such conditions, traditional reactive management approaches are no longer sufficient to ensure business resilience and long-term competitiveness. This determines the relevance of risk-oriented management as a systemic tool for integrating risk assessment into strategic and operational decision-making.

Methods. The study is based on general scientific and special research methods, including system and structural-functional analysis, comparative analysis, generalisation, expert assessment and scenario analysis. The information base comprises statistical data, analytical reports of national and international institutions, as well as recent academic studies on enterprise risk management. A multilevel approach to risk analysis was applied, covering strategic, tactical and operational management levels.

Results. The paper substantiates the feasibility of transitioning from fragmented risk management practices to integrated risk-oriented management models adapted to wartime conditions. Key categories of risks affecting Ukrainian enterprises are systematised, and a system of risk monitoring indicators is proposed. These indicators enable timely identification of critical threats, improve the quality of managerial decisions and contribute to enhancing the economic resilience and adaptability of enterprises in an unstable environment.

Discussion. The findings confirm that the implementation of integrated risk-oriented management supports not only loss minimisation but also the identification of strategic opportunities under conditions of prolonged uncertainty. Further development of this approach requires the integration of digital technologies, Big Data and artificial intelligence into risk monitoring systems, as well as alignment of enterprise risk management practices with European regulatory standards.