Data Envelopment Analysis of sustainable development performance with enterprise structure and data governance in Europe

This study examines how efficiently the 27 EU member states advance SDGs 8, 9, and 12, and whether SME prevalence is associated with differences in sustainability efficiency. Using indicators from the UN SDG Global Database and SME data from Eurostat, we apply an output-oriented Slacks-Based Measure DEA model under Variable Returns to Scale, complemented by slack analysis, correlation analysis, and a FAIR assessment of the primary SDG dataset. The results reveal marked cross-country heterogeneity. For SDG 8, inefficiencies are concentrated in labour-rights compliance, unemployment, and fatal occupational injuries. For SDG 9, the main shortfalls concern research and development expenditure and manufacturing employment, while for SDG 12 they concern waste management, recycling, renewable energy capacity, and tourism accounting tools. SME prevalence is most strongly associated with SDG 9 indicators, especially research and development and carbon emissions, while links to SDGs 8 and 12 are weaker. The FAIR assessment shows strong accessibility and metadata quality, but weaker interoperability and licensing clarity. These findings suggest that policymakers should target the specific indicator gaps that constrain performance and align SME support with greener innovation, emissions management, and stronger reporting capacity. The paper therefore treats sustainable development performance as a multidimensional efficiency construct rather than as a single aggregate score, and interprets DEA results as relative benchmarking evidence rather than causal estimates of national sustainability performance.