The long term evolution of science and technology has increasingly become one of the most central concerns in economic theory, innovation studies, and science policy. Over the last century, scientific knowledge has shifted from being a largely artisanal, individual driven activity to a highly institutionalized, networked, and globally distributed system of production. This transformation has been accompanied by a parallel evolution in technologies, where incremental improvements coexist with radical and disruptive changes that reshape entire industries and societies. The central objective of this research is to integrate and extend theoretical perspectives on the evolution of science, technological change, and innovation using a unified analytical framework grounded in evolutionary economics, scientometrics, and technological paradigms. Drawing exclusively on the literature of Coccia and associated scholars as well as foundational theories by Kuhn, Lakatos, Price, Crane, and Fortunato, this study constructs a comprehensive model that explains how scientific fields emerge, grow, converge, and decline while generating technological breakthroughs and economic long waves.

This research demonstrates that science advances through cumulative, competitive, and convergent processes that are shaped by institutional structures, funding mechanisms, and international collaboration networks. Scientific paradigms, as described by Kuhn, do not evolve in isolation but are embedded in broader techno economic systems where knowledge production interacts with industrial demand, political governance, and social needs. Coccia’s theory of technological parasitism further clarifies how new technologies grow by exploiting the infrastructure and knowledge bases of previous technologies before either coexisting with or displacing them. These dynamics explain the asymmetry of technological cycles, where rapid emergence is often followed by slower diffusion and stabilization, and why some technologies become general purpose technologies that trigger long term economic growth.

Using bibliometric, scientometric, and patent based conceptual methods, the article synthesizes insights from research on quantum technologies, artificial intelligence, sensor technologies, and converging scientific fields to show how emerging technologies are not isolated phenomena but products of complex interactions among research funding, scientific collaboration, and institutional learning. The results highlight that countries and organizations that successfully coordinate basic research, applied research, and technological development are more likely to generate disruptive innovations that lead to industrial leadership. At the same time, excessive concentration of resources or overemphasis on applied research can undermine long term scientific creativity and reduce the probability of radical breakthroughs.