Donato Iacobucci (p)

Francesco Perugini

The concept of connectivity proposed by the European Commission in the guide to S3 implementation foresees a strong interaction between European regions in sharing and exchanging research and innovation. This basically implies looking for somehow related specialisation patterns beyond the regional administrative boundaries which have the potential to be combined with regional ones.
Up to now, very few regions have considered connectivity in the design of their S3 strategy. In fact, the lack of data and the absence of a clear methodology discouraged regions from attempting to analyse and measure any potential connection with potential European partners, neither within national boundaries.

Using patent data to categorize technological domains in each region, the aim of our work is to explore and empirically assess different measures of connectivity. In particular, we look both at measures of similarity and complementarity between European regions. Similarity refers to the degree of resemblance in terms of relative specialisation in technological domains between regions. Complementarity is related to the combinatory potential of the technological domains of pairs of regions and it is based on the aforementioned concept of relatedness. In order to understand whether these two dimensions of connectivity are related to the actual collaboration behaviour of EU regions, we look at past EU funded project that preceded the implementation of Smart Specialisation Strategy, namely those under the Seventh Framework Programme.
Using the pairs of regions as observations, we look at the probability that two regions collaborate in EU projects (namely a standardized measure of co-occurrence) is related to the similarity and the complementarity between the technological domains in which they are specialised.

Controlling for a number of characteristics of regions, we find that distance has a negative effect on collaboration and being in the same country of in the same NUTS1 are positively related. Our measures of connectivity seem to play a significant role in affecting the probability of collaboration, but while the degree of similarity is positively associated to the collaboration between region the degree of complementarity has the opposite effect. These findings suggest that regions tend to establish collaborations when they are technologically similar to each others but not when their technological specialisations show high relatedness, and supposedly high combinatory potential. From a policy perspective, these results raise questions about both the rationale and the implementation of connectivity strategies as suggested by S3 guidelines.

Francesco Perugini (p), Donato Iacobucci, Diego D'Adda

Krzysztof Mieszkowski

The design of a Smart Specialization Strategy (S3) was an EU conditionality for the allocation of structural funds (ESIF) to regions for the programming period 2014-2020. Regions were not only required to elaborate and declare a specific strategy for the allocation of ESIF funds but also to follow a set of rules for its elaboration and design. For the elaboration of the strategy the major novelty was the involvement of major stakeholders, in the logic of the quadruple helix, and the emphasis on the entrepreneurial discovery process in the selection of promising sectoral and technological targets where to concentrate resources. In fact, the other major novelty of S3 was the emphasis on the concentration of public funds in few domains in which the region may gain a competitive advantage in production and innovation (specialization). These domains were expected to be chosen according to the actual strengths of the region (thus the smart nature of the strategy)
Up to now, the literature on S3 has devoted its attention on discussing the rationales for this strategy and how the process was implemented by EU regions. Today, after a few years of implementation of S3, we have some figures to assess first outcomes. In this work, we aim at assessing to what extent S3 implementation changed the investment strategy of regions as compared with the previous programming period.

Krzysztof Mieszkowski (p), Javier Barbero

Donato Iacobucci

Smart specialisation is a place-based policy approach which asks regions or countries to define the main strategic domains for research and innovation investments. Smart specialisation seems to offer policy makers a new integrated set of principles guiding investment in innovation through prioritisation and concentration of public resources, and the mobilisation of local assets and entrepreneurial capacity. European Commission regional policy grounded in the place-based approach made available the largest, pan-European industrial policy funding programme to apply those principles.
In our paper we try to handle some critical for smart specialisation issues like the acquisition and transition of knowledge and ideas at the geographical level, the existing defragmentation of regional systems of innovations, the multi-level governance framework of smart specialisation implementation, the dependence of each territory on its specific characteristics. With our work we think we can contribute to an analytical framework to monitor the regional variations during the smart specialisation implementation systematically.
For this purpose we analyse the 4,276 research and innovative projects in Poland in the mid-term of operational programmes implementation stage. They have been supported with grants or vouchers coming from the European Regional Development Fund and contracted under the Polish smart specialisation framework. First, we explore difference in policy mixes at national and regional level. Then, if there is a territorial concentration of smart specialisation projects. Finally, we look if smart specialisation has a regional or rather urban or rural territorial perspective associated with some factors characterising the projects’ locations.
Our empirical analysis confirm the concentration of research and innovation investments in cities and that the smart specialisation implementation is affected by agglomeration of innovative activities in urban territories in Poland. The Polish main cities seems to match local research strengths with business needs and to build critical mass in terms of population, entrepreneurial potential, size of output of innovative activities measured by patents application as associated factors, but also their functions as capital of regions and state for generating research and innovation projects. These findings might signal a need to expand this inclusion in territorial sense either by the revision of the smart specialisation domains in order to expand their spatial dimension or by the improvement of the implementation mechanisms supporting the development of smart specialisation domains in less attractive and active territories.