Configuration Paths to Efficient National Innovation Ecosystems

• A novel two-step model extending traditional DEA using fsQCA. • Configuration pathways to efficient cooperation, innovation, and knowledge creation. • ICT investments and education level are prerequisites for efficient NIEs. • A suitable R&D subsidy mix enables avoiding crowding-out effects. Efficient National Innovation Ecosystems (NIEs) create appropriate conditions for the generation of new knowledge, collaboration, and innovation, which are key determinants of countries’ economic growth and competitiveness in the era of a globalized, knowledge-based economy. Prior studies have therefore focused on measuring both the efficiency of NIEs and key attributes occurring within them. This has led to the assessment of countries in terms of their ability to effectively convert inputs into outputs and has provided a benchmark for less successful economies and their NIEs by using Data Envelopment Analysis (DEA) and its modifications. However, while these methods have measured the efficiency of individual economic entities, they do not show how to achieve this efficiency. Therefore, we propose a novel, hybrid two-step model combining DEA and fuzzy-set Qualitative Comparative Analysis. This enables us to examine the relationships between all possible combinations of inputs and outputs within the NIEs of OECD countries and to identify configuration paths showing how to achieve effective outputs in terms of cooperation, knowledge creation, and innovation. We also show that countries could benefit from multiplication and crowding-in effects emerging from combinations of different R&D expenditures rather than from one financial source.