Building an ANFIS-Based Decision Support System for Regional Growth: The Case of European Regions

Abstract

This paper proposes an adaptive network fuzzy inference system (ANFIS) based decision support system that can provide European policy makers with systematic guidance in allocating and prioritizing scant public resources, whilst accomplishing the best growth performance at a regional level. We do so by taking the stance of the Smart Specialization Strategies, which aim at consolidating the regional strengths and make effective and efficient use of public investment in R&D. By applying the ANFIS method, we were able to understand how - and to what extent - the competitiveness drivers promoted technological development and how the latter contributes to the economic growth of European regions. We used socio-economic, spatial, and patent-based data to train, test, and validate the models. What emerges is that an increase of R&D investments enhances the regional employment rate and the number of patents per capita; in turn, by taking into account the several combinations of specialization and diversification indicators, this leads to an increase of the regional gross domestic product (GDP).