Why do we need to complement the European Union Regional Innovation Scoreboard with an artificial intelligence tool for what-if policy analysis?

TL;DR

This paper proposes integrating an artificial intelligence tool with the European Union Regional Innovation Scoreboard to enhance regional innovation policy analysis through better grouping and what-if policy simulations.

Contribution

It introduces a combined factorial K-means and neural network approach to improve regional grouping and policy impact analysis beyond the existing EURIS methodology.

Findings

Proposed grouping methods create more homogeneous regional clusters.

Neural network-based simulations help assess policy effectiveness.

Methodology shows potential for better regional innovation policy planning.

Abstract

The European Union Regional Innovation Scoreboard (EURIS) is currently and broadly used for the definition of regional innovation policies by European policymakers; it is a regional innovation measuring tool for the analysis of each specific innovation indicator, from which it is possible to analyze the overtime evolution of each regional innovation indicator; according to the importance of the European Union Regional Innovation Scoreboard for innovation policy purposes, we state that European regional policymakers need integrative and synergistic methodological tools, with respect to the EURIS one, for innovation policy purposes. We state the need to integrate the current methodology of the European Regional Innovation Scoreboard with a Factorial K-means (FKM) tool for grouping purposes, and with a neural network (NN) tool for performing what-if policy analyses. Experimental results suggested that our proposed grouping/labeling methodologies are able to develop more compact groups, resulting in regions having better similarities, than the ones developed by the EURIS methodology. Experimental simulations, within the framework of our proposed what-if tool, highlight the potential usefulness of our methodological tool (neural network-based) for the understanding of the potential effectiveness of each possible and specific regional innovation policy to be implemented. We claim that our proposed FKM-NN tool could be used, by regional innovation policymakers, as a very effective synergistic instrument of the European Union Regional Innovation Scoreboard.