A multidimensional quadrant-based methodological framework for system assessment: the case of national R&D systems

Comparative assessment of complex social systems is commonly based on composite indices and linear rankings that aggregate heterogeneous indicators into single-dimensional scores. While such approaches facilitate benchmarking, they often obscure structural configurations, internal asymmetries and multidimensional system profiles. This paper proposes a multidimensional quadrant-based methodological framework designed to support comparative system assessment without collapsing information into a single composite index. The framework restructures selected indicators into a two-dimensional coordinate space defined by autonomous but interrelated analytical dimensions and positions systems relative to an explicit reference benchmark. By relocating the coordinate origin to a reference configuration, the approach enables scale-independent comparison and transparent identification of system configurations through quadrant-based classification. The framework is conceived as a diagnostic and classificatory tool, rather than a causal or predictive model, and is applicable across domains characterised by heterogeneous indicators. The methodological logic of the framework is illustrated through an application to national research and development (R&D) systems, where one dimension captures a synthesised representation of system capacity, while the second reflects structural characteristics of human resources composition. The illustrative application demonstrates how the proposed framework reveals structural differences between systems that may remain hidden in conventional composite indicators or rankings. By offering a coordinate-based, non-aggregative alternative to composite index approaches, the proposed framework contributes to methodological debates on multidimensional measurement, system classification and comparative analysis in the social sciences.