B-MIDIA: A Belief-Structure Multi-Criteria Decision Framework for Analyzing Citizens’ Perceptions of Digital Technologies in the European Union

Digital technologies are reshaping economies, labor markets, social security systems, and societal well-being across the European Union, increasing the need for decision-support methods capable of systematically analyzing complex survey evidence. This study proposes B-MIDIA, a parametric extension of the belief-structure TOPSIS framework that integrates the MIDIA (Multi-Criteria Method Integrating Distances to Ideal and Anti-Ideal Points) aggregation mechanism with belief-structure-based multi-criteria decision analysis. The framework preserves the ordinal structure of survey responses and follows the standard belief-structure representation adopted in B-TOPSIS, in which uncertain (“Don’t know”) responses are incorporated into the evaluation through the normalization procedure. Using published country-level response distributions from Special Eurobarometer 554, the study evaluates public perceptions of recent digital technologies, including artificial intelligence (AI), across EU Member States in five domains: the economy, society, quality of life, current job, and social security benefits. Sensitivity analyses performed for alternative values of the aggregation parameter α, together with comparisons with the benchmark B-TOPSIS rankings, demonstrate the robustness of the proposed aggregation mechanism within the adopted belief-structure framework. Across most dimensions, Lithuania and Malta achieved the highest evaluations, whereas France, Italy, and Romania generally ranked among the lowest. Economic and employment-related evaluations formed the central perception structure and were strongly associated with quality-of-life assessments. The proposed framework extends the analytical capabilities of belief-structure TOPSIS by enabling systematic sensitivity analysis of aggregation assumptions while preserving methodological compatibility with the original framework.