How Research Variability Drives Technological Evolution for Fostering and Managing Emerging Innovations

Abstract Understanding how variability in research topics influences scientific and technological evolution remains underexplored in the economics of science and innovation. This study investigates how the variability within and between research fields affects scientific and technological trajectories, with implications for innovation management. Using entropy and standard deviation measures, and variance decomposition method, we analyze four emerging domains in quantum science and technology: quantum optics, metrology, imaging, and sensing. Results indicate that quantum optics exhibits lower variability in scientific topics and more stable evolutionary paths (entropy H = 0.83), whereas quantum sensing demonstrates higher scientific variability and dynamic development ( H = 0.93). Variance decomposition reveals that 91.7% of variability occurs within research fields, underscoring internal diversity as a key evolutionary driver. Complementary patent analysis supports these findings. These findings have main implications for strategic management and technological policy based on an ambidexterity strategy given by exploration activities in scientific and technological fields having high variability in research topics and as a consequence uncertain directions of technological pathways, whereas exploitation managerial practices fostering scientific and technological development in fields having lower variability between research topics with more stable directions. Hence, these insights offer theoretical contributions to the understanding of basic drivers in scientific and technological evolution, and implications of management for R&D strategy, science and innovation policy in emerging technologies to support competitive advantage of firms and nations.