Brain economy and the entrepreneurship gap

Purpose This study aims to develop an integrated, efficiency-based framework to evaluate how European Union (EU) member states transform brain-economy capabilities into entrepreneurial outcomes. While existing indicators measure human capital, innovation, digitalisation or entrepreneurship separately, little is known about how efficiently these capabilities are converted into total early-stage entrepreneurial activity (TEA). The authors address this gap by introducing a multidimensional Brain Economy Index (BEI) and a family of brain-economy-to-entrepreneurship efficiency (BEEE) models to examine the cognitive–entrepreneurial divide across the EU. Design/methodology/approach Using harmonised panel data for 27 EU countries (2004–2024), they construct the BEI and three pillars – Human Capital and Skills (HCS), Innovation and Knowledge Creation (IKC) and Digital–Cognitive Infrastructure (DCI) using a Data Envelopment Analysis (DEA) approach. In a second stage, they estimate five efficiency models (BEEE, BEEE-Three-Subindex, Human-Capital-and-Skills-to-Entrepreneurship Efficiency, Innovation-and-Knowledge-Creation-to-Entrepreneurship Efficiency, Digital–Cognitive-Infrastructure-to-Entrepreneurship Efficiency) to assess how efficiently countries convert brain-economy capabilities into TEA Findings Results reveal a persistent North–South and West–East divide in brain-economy capability stocks, with Nordic and Western economies forming the capability frontier. However, entrepreneurial conversion efficiency follows a different pattern: Estonia, Slovakia, Latvia, Lithuania and Cyprus define the efficiency frontier, while several capability-rich Western economies exhibit structural inefficiencies. Temporal analysis shows convergence in human capital and digital infrastructure but persistent asymmetries in innovation capability. Overall, the evidence identifies a clear cognitive–entrepreneurial divide within Europe. Research limitations/implications The study focuses on EU member states and relies on available cross-country indicators; certain intangible or cognitive-capital measures could not be included due to data constraints. Future research may extend the framework to emerging economies, incorporate institutional-quality variables directly into the efficiency frontier or apply dynamic DEA approaches to capture intertemporal spill-overs and ecosystem evolution. Practical implications Findings suggest that expanding human capital, R&D and digital infrastructure alone is insufficient to stimulate entrepreneurship. Policymakers should complement capability investments with ecosystem reforms that reduce regulatory frictions, enhance risk financing and accelerate knowledge commercialisation. Targeted policies improving conversion mechanisms may yield higher entrepreneurial returns than further resource accumulation alone. Social implications By identifying structural inefficiencies in the translation of cognitive resources into entrepreneurship, the study highlights pathways to strengthen inclusive growth, job creation and regional cohesion within Europe. Improving entrepreneurial conversion efficiency may help reduce territorial disparities and enhance long-term socio-economic resilience. Originality/value This paper offers systematic efficiency-based BEI and a family of BEEE models. It advances entrepreneurship research by shifting the focus from capability accumulation to capability conversion, providing systematic evidence of a cognitive–entrepreneurial divide in Europe. The framework offers a new analytical lens for studying entrepreneurial ecosystems in advanced and emerging economies.