Selecting data envelopment analysis models: A data-driven application to EU countries

Data envelopment analysis (DEA) is a non-parametric data-driven approach for evaluating the efficiency of set homogeneous decision-making units (DMUs) with multiple inputs and outputs. The number performance factors (inputs outputs) plays crucial role when applying DEA to real-world applications. In other words, if significantly greater than DMUs, it highly possible arrive at large portion efficient which practically may become problematic due lack ample discrimination among DMUs. current research aims develop an array selecting models narrow down based upon rule thumb. To this end, we show that input- output-oriented select different then present integrated identify common both orientations. addition evaluation individual level, study structural single production unit industry level. Finally, case on EU countries presented give insight into business innovation, social economy growth regard entire EU.