Scientometric indicators as tools for evaluating innovation and research productivity

Abstract

This article explores the role of scientometric indicators as tools for evaluating innovation and research productivity in contemporary science systems. Drawing on the evolution of scientometrics from early citation analysis to advanced computational methods, the discussion highlights how indicators provide insights into the structure of knowledge production, the flow of ideas, and the translation of research into innovation. The analysis emphasizes the dual function of scientometric indicators in assessing both productivity, measured through publication and citation outputs, and innovation, reflected in interdisciplinary connections, knowledge transfer, and societal impact. The article also examines the limitations of relying solely on quantitative indicators, including disciplinary differences, methodological biases, and unintended behavioral consequences. By considering the integration of bibliometric data with patents, funding records, and alternative metrics, it argues for a balanced approach that combines quantitative measures with qualitative evaluations. The conclusion underscores the necessity of responsible and contextualized use of scientometric indicators to guide research policy, institutional strategy, and global collaboration in advancing innovation.