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СтаттяЗовнішня публікація🌐 Ukrainian

Trending Models of Managerial Decision-Making: From Ideal to Gender-Oriented

Svitlana Gazaryan

Анотація

This article presents a critical analysis of the evolution of managerial decision-making models in the public sector within the context of contemporary transformations: technological revolution, demographic changes in Ukraine’s civil service, and wartime challenges. The study traces the theoretical trajectory from Weber’s classical rational model to modern adaptive and hybrid models, including Simon’s bounded rationality model, Lindblom’s incremental model, Etzioni’s mixed-scanning model, Cohen-March-Olsen’s garbage can model, and the coalition model. A comparative analysis of models is conducted based on epistemological foundations, key assumptions about decision-makers, critical limitations, and optimal application domains. Particular attention is paid to analysing contemporary models utilizing artificial intelligence and adaptive approaches within Bauman’s concept of “liquid modernity.” The author proposes a gender-oriented decision-making model that accounts for the influence of socially constructed behavioural patterns on managerial practices. The model comprises eight cycles: emotional reaction, problem definition, goal formation, alternative generation, decision selection, implementation, monitoring, and reflection. The methodological limitations of the proposed model are critically analysed, including risks of essentializing gender differences and the problem of within-group variability. The study demonstrates that under conditions of martial law and personnel transformations in Ukraine’s civil service (reduction of 50,000 employees, 75% female dominance in positions), a hybrid approach integrating elements of various models depending on specific managerial situations is optimal. Prospects for empirical verification of hybrid model effectiveness and development of methodology for assessing the correspondence between decision-making models and specific managerial challenges are identified.

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