Abstract Various analytical frameworks, such as the National Innovation System (NISs) and N-tuple innovation helices, have been developed to address technological change at a spatial or sectoral-technological level. Several quantitative methodological approaches have been used to capture the effectiveness, efficiency, and overall performance of innovation at the national level. Reviewing these approaches, we highlight important aspects of the innovation process, such as actor heterogeneity, the intensity of interactions, and evolutionary dynamics within and between innovation subsystems that are often underestimated. We conceive NISs consisting of five interacting helices: government, academia, industry, society, and finance. Actors belonging to these helices develop their behavior – in terms of resource commitment/allocation – in the context of interdependencies and interactions that condition the effectiveness and efficiency of their actions. As a result, their expectations are formed from their perception of how other actors and the system behave. We develop a conceptual framework that goes beyond the static illustration of ‘innovation scoreboards’ and linear models. It illustrates how individual parameter changes – in one helix of the system – may generate non-linear effects throughout. We use a causal loop diagram (CLD) to depict the intricacies of the interactions amongst various elements in NISs, and a stock-and-flow diagram (SFD), which forces more detailed specification of causal mechanisms. Our framework facilitates helix-based actor heterogeneity and highlights the key causal mechanisms and feedback loops – set in motion from actor interactions – that govern NIS’s evolution and performance without losing oneself in immense detailed complexity.
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