Workforce Composition as a Structural Dimension of Innovation Systems: A Configurational Systems Analysis of Capacity and Participation

Innovation systems are commonly analysed through indicators of investment, performance, technological capacity, and research output, while less attention is paid to the composition of the research workforce. This article asks whether workforce composition can be understood as a structural dimension of national innovation systems and whether it is systematically associated with their capacity configuration. Using comparative 2023 data for 28 European and selected non-European national R&D systems, the study combines correlation analysis, a multidimensional capacity coordinate, and quadrant-based configurational mapping. Innovation-system capacity is operationalised through R&D intensity, innovation performance, and R&D expenditure per researcher. Workforce composition is measured by the share of women among researchers and is treated as a separate aggregate dimension rather than as a comprehensive measure of substantive inclusion. The results indicate a recurrent negative association between innovation-system capacity and the relative representation of women among researchers. Higher-capacity systems are more frequently positioned in configurations characterised by lower female representation, although cases combining high capacity with higher representation demonstrate that the pattern is not universal. The study does not establish causality, temporal development, or a deterministic trade-off. Sectoral, disciplinary, institutional, educational, and cultural factors may contribute to the observed cross-national differences. The article contributes to innovation-systems research by integrating aggregate workforce composition into systems-level analysis and by demonstrating how coordinate-based configurational mapping can reveal relationships that remain obscured in composite rankings.