Optimising Sustainable Development in Europe DEA-Based Efficiency Assessment with SME Integration

Sustainable Development Goal (SDG) are central to the European Union (EU)’s policy framework, yet assessing progress remains complex due to the multidimensional nature of SDG data and national disparities. This thesis investigates the efficiency of EU member states in achieving SDGs 8 (Decent Work and Economic Growth), 9 (Industry, Innovation, and Infrastructure), and 12 (Responsible Consumption and Production) by applying a Slacks-Based Measure (SBM) Data Evelopment Analysis (DEA) model under Variable Return to Scale (VRS) asssumption.The study evaluates how efficiently countries convert inputs such as resource consumption and emissions into desirable outputs like waste recycling and renewable energy capacity. A key contribution is the integration of Small and Medium-sized Enterprises (SME) data into the analysis, exploring their role in shaping SDG performance. The research also applies Findable, Accessible, Interoperable, and Reusable (FAIR) data principles to assess the quality and usability of the United Nations (UN) SDG database. Spearman rank analysis is employed to assess the relationship between SMEs and SDG indicators. Findings reveal significant disparities in efficiency across EU countries, highlight specific areas for improvement through input-output slack analysis, and show the relevance of SMEs in achieving SDG targets. This study contributes a novel approach to SDG assessment by combining DEA with SME integration, offering actionable insights for policy-makers to enhance SDG performance across the EU