Technologies as an emergent factor of economic transformations

Анотація

This article explores the role of technologies as an emergent factor in contemporary economic transformations. The study focuses on the interdependence of digital innovations, capital, and socio-economic systems, which are shaping a new economic reality through mechanisms of self-organization, co-evolution, and nonlinear development. Technologies such as artificial intelligence, blockchain, the Internet of Things (IoT), and others are no longer merely tools but have become agents of transformation in market structures, organizational forms, and the institutional environment. The paper proposes viewing the economy as a complex adaptive system that evolves through emergent mechanisms, including network effects, decentralization, integration of management functions, and the development of digital infrastructure. It is shown that innovation has moved beyond being solely the outcome of research and development (R&D); instead, it emerges from the dynamic interaction of knowledge, needs, and technologies within complex environments. Modeling economic processes from the perspective of emergence enables a more adequate understanding of modern nonlinearity, multi-level structure, and variability. The article investigates the economic origins of emergent models of innovative development, emphasizing that such models arise not from linear improvements to existing structures but from the dynamic interplay of capital, technology, and institutions within innovation ecosystems. Particular attention is given to the mechanisms of self-organization and synergy that provide adaptability and resilience in the new economy under conditions of global change. Additionally, the study examines innovation ecosystems as foundations for developing new business models, digital platforms, and knowledge clusters. The authors demonstrate that classical economic models are no longer capable of fully capturing the dynamics of today’s economy and instead advocate for approaches based on complexity theory and network dynamics.

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