Факультет економіки і менеджменту (ДМетІ)

Permanent URI for this communityhttp://crust.ust.edu.ua/handle/123456789/14591

ENG: Faculty of Economics and Management (DMetI)
Dnipro Metallurgical Institute

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Adaptive Management of Regional Innovation Ecosystems Based on Hybrid Intelligent Support Systems
(Ukrainian State University of Science and Technologies, Dnipro, 2026) Deliiev, S. K.; Zavhorodnia, Olena O.
ENG: This study addresses the optimization of innovative development management within regional smart ecosystems. Unlike traditional management approaches, the author proposes a transition to adaptive governance based on Hybrid Decision Support Systems (HDSS). The research redefines the role of the manager in a digital environment, shifting focus from intuitive decision-making to data-driven strategic planning. By integrating Fuzzy-AHP methodology and cloud-native infrastructure, the study provides a framework for managing the lifecycle of regional innovations. The results demonstrate that hybrid intelligence effectively reduces information entropy and enhances the strategic flexibility of regional innovation systems.
Smart-Projects of Regional Development: Content, Taxonomic Identifiers, and Project Management Specifics
(Ukrainian State University of Chemical Technology, Dnipro, 2025) Deliiev, S. K.; Zavhorodnia, Olena O.
ENG: This research examines the theoretical and methodological foundations of initiating, developing, and implementing smart-projects of regional development as a unique form of implementing the smart economy concept on the regional level. This research builds on the fundamental concept of human-machine intellectual systems. It presents an original interpretation of the “smart-project for regional development” concept and develops a system of taxonomic identifiers. These identifiers clearly differentiate smart-projects from ordinary digitalization initiatives. This research defines seven attributive characteristics that form the content of smart-projects: intellectual core, knowledge-information orientation, adaptive potential, synergistic properties, integrative architecture, transformational capability, and cognitive processes. This study develops a classification matrix of smart-projects based on their smart component development level, with clear criteria for each level and subsequent categorization into four functional groups: “traditional projects,” “projects with digitalization elements,” “entry-level smart-projects” and “advanced smart-projects.” The paper examines smart project management features, analyzing modifications to the project and management cycles, differences in decision-making tools, and methodological approaches to forecasting and evaluating project effectiveness and efficiency. Practical recommendations are formulated for identifying and implementing smart-projects on the regional level. The research results have significant theoretical and practical value for developing and implementing smart specialization strategies for Ukrainian regions within the context of current global economic transformations.