Application of the PROperty FITting Method (PROFIT) to Classification of EU Countries Based on Their Innovation Level

As it is known, innovativeness can be measured by using many known indices, such as the Global Innovation Index, the Summary Innovation Index, etc. and often these indices are based on different methodologies and take into consideration different sets of diagnostic variables. As a consequence, the final evaluation of innovativeness may strongly depend on the innovation index used. Obviously, some groups of indices lead to similar ranks of the EU countries. Nevertheless, if there are at least two groups of indices which provide different ranks of these countries, a problem with the proper evaluation of their real innovativeness arises. One of the solutions is to select the most valuable indices by observing the impact of all indices on forming distances between innovativeness levels of the EU countries. Following this option, the main aim of this paper is classification of the EU countries with respect to their innovativeness and the evaluation of international index influences on the classification obtained. The aim of the paper is to conduct the research on differences in innovation intensity across the EU member countries. For the purpose of the article, the PROFIT (PROperty FITting) method, an extension of multidimensional scaling (MDS), was applied. The ultimate goal of MDS techniques is to produce a geometric map that illustrates the underlying structure of complex phenomena, for instance, innovativeness of the EU countries. It is a widely used method which collects attribute ratings for each object (country) and then finds the best correspondence of each attribute to the derived perceptual space. Applying the PROFIT method needs linear regression techniques and provides some additional information, i.e. the impact of the considered set of diagnostic variables on the shape of the perception map. The final result is a two-dimensional map of the EU countries which reflects distances among their innovativeness levels along with vectors presenting the influence of international indices of innovativeness on the structure of this map. The nature of the results and the ways in which they are interpreted are subsequently reviewed. The main conclusion drawn from the perception map created concerns the interpretation of the above-mentioned vectors, i.e. the information about the role of each international innovation index in clustering the EU countries with respect to their innovation intensity is obtained.