# 33 182-188 View full article

УДК 330.341.1:339.9

DOI: https://doi.org/10.36887/2415-8453-2026-1-33

Yemchenko Maksym,
graduate student,
National University of Bioresources and Nature Management of Ukraine,
https://orcid.org/0009-0008-3385-3727

JEL classification: O31, O32, R11, R58

Published: 25.02.2026

The article examines the conceptual foundations of adaptive innovation management based on knowledge spillover effects in regional clusters. Traditional approaches to innovation management focus on internal research and development of individual firms, ignoring the fact that a significant part of innovation value is created through inter-organizational interaction and knowledge exchange mechanisms. Recent empirical evidence demonstrates a fundamental shift in understanding innovation processes: approximately 85% of inventors work in firms with establishments in multiple technology clusters, suggesting that organizational proximity may be more important than geographical proximity for knowledge transfer. The research shows that the greatest difference between social and private returns to innovation is observed not in the largest, but in the best-connected clusters. This finding has critical implications for cluster policy: instead of concentrating resources on building giant clusters, a more effective strategy may be to maximize connectivity between existing regional clusters through systematic knowledge exchange mechanisms, labor mobility programs, and joint research projects. For example, Atlanta ranks first in terms of the social-private returns gap due to high inter-cluster connectivity, despite being smaller than Silicon Valley in absolute size. A three-level adaptive management model is proposed, which includes the micro-level (individual cluster participants), meso-level (cluster organization as coordination center), and macro-level (regional innovation system). The model integrates five interconnected components: a system for measuring spillover effects, a knowledge exchange platform combining digital and physical infrastructure, mechanisms for stimulating cooperation that balance incentives with intellectual property protection, competence development programs to enhance absorptive capacity, and an adaptive management loop based on the Monitor-Analyze-Decide-Act-Learn (MADAL) cycle with quarterly iterations. The research results have practical significance for developing cluster policy, regional innovation strategies, and managing innovation ecosystems.

Keywords: knowledge spillovers, innovation cluster, adaptive management, inter-organizational collaboration, regional innovation system.

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Quote article, APA style

Yemchenko M. Adaptive innovation management through knowledge spillovers: a cluster-based framework. Ukrainian Journal of Applied Economics and Technology. 2026. №1. 182-188 pp. https://doi.org/10.36887/2415-8453-2026-1-33

Quote article, MLA style

Yemchenko M. Adaptive innovation management through knowledge spillovers: a cluster-based framework. Ukrainian Journal of Applied Economics and Technology. https://doi.org/10.36887/2415-8453-2026-1-33