Robust measurement of innovation performances in Europe with a hierarchy of interacting composite indicators

Abstract

For a long time, the measurement of innovation has been at the forefront of policymakers' and researchers' agenda worldwide. Therefore, there is an ongoing debate about which indicators should be used to measure innovation. Recent approaches have favoured the use of composite innovation indicators. The European Innovation Scoreboard (EIS) is a relevant tool for benchmarking innovation in Europe. Still, the EIS lacks a proper scheme for weighting the included indicators according to their relative importance. Moreover, despite there is a consensus on the importance of interaction between different dimensions of innovation, there is no composite indicator taking into account of this. We propose an appraisal methodology permitting to take into consideration the interaction of dimensions to be aggregated and robustness concerns related to the elicitation of the weights assigned to the elementary indicators structured in a hierarchical way. With this aim, we apply a multiple-criteria decision-making approach being the conjunction of three methodologies, namely, the multiple-criteria hierarchy process, the Choquet integral and the stochastic multicriteria acceptability analysis. It helps the users to rank and benchmark countries' innovation performance at partial and global level taking into account the importance and interaction of dimensions as well as robustness concerns.