Policy makers are being confronted with complicated and rationally chaotic systemic analytical models of regional innovation that could not easily be applied due to the absence of cross regional data to map these models. The systemic analysis of innovation systems conceives complex analytical frameworks, with intense socio-technological aspects of knowledge generation and encompasses a detailed analysis of system failures. These frameworks are not suitable for benchmarking a wide range of regions, due to low availability of such elaborate data sources. On the other hand, metric regional innovation micro data offer the opportunity for large-scale cross-regional benchmarking exercise illustrating mainly the market failures of the innovation systems although this type of analysis does not provide any detailed systemic envisioning. Would it be possible to develop an analytical model having the sufficient specificity of the systemic approach, limited by the availability of cross regional micro data that map the processes of this model? Would it be able to demonstrate a sufficient level of systemic abstraction, restricted to the level of the availability of data to map specific system interactions? These are the main challenges addressed by 3I.
The 3I model matches the metric indicators with relative system interactions, constructing a systemic analytical framework of analysis. The metric system that was used to extract micro data is the European Innovation Survey. The analysis concluded ten interactions, which form a system with the corresponding regional actors. (nodes). Thus, the entire function of the systemic theory, being efficiency, effectiveness and cost assessment could be potentially applied to the system interaction and nodes.
Regional policy makers could apply the 3I model to prepare appropriate innovation policies to strengthen the weak interactions of a region. The regions must enforce specific and targeted policies to reach excellence. Balancing innovation resources and enforcing certain innovation policies in specific regions are some of the findings of this approach.