Regional Innovation Systems as Complex Adaptive Systems: The Case of Lagging European Regions

Abstract

This article proposes an agent-based model to support the development of self-sustaining regional innovation systems (RIS). The model is the base of a computational laboratory, CARIS (Complex Adaptive Regional Innovation System), which aims at evaluating the self-sustainability of RIS and at investigating what are the resources, competencies and mechanisms able to trigger powerful innovation and economic growth processes. Such a topic is particularly interesting for the so-called lagging regions, which, notwithstanding noticeable policy interventions, have been unable to significantly improve their innovation performances. Results of this study show that the exploration capacity, the propensity to cooperation, and the endowed competencies of actors belonging to a region could be considered as key aspects in affecting the regional innovation performance. This means that policy-makers should (i) incentivize investments in research and development activities both at the public and private levels; (ii) support public-private partnerships; (iii) enhance national and regional university systems; and (iv) increase the number of researchers employed both in the public and private sectors. In the next future, the CARIS laboratory could be adopted as policy support instrument to evaluate how much effective are current innovation policies and what are the most effective ones to reassess the current patterns.