Guide to Research and Innovation Strategies for Smart Specialisation

3. 'Cluster' in-depth case studies and peer reviews: to move beyond the figures that are
available in a comparative way, more qualitative studies can be carried out on activity
domains where a region shows relative specialisation. This involves expert work on value
chain analysis (undertaken in an international perspective and enlightening the spatial
division of labour), context conditions for the operation of the cluster, labour market
situation, etc. It also involves an analysis of the linkages between the cluster and other
clusters or industries, in order to examine whether one can talk about related variety across
the areas of regional specialisation. One interesting approach is that of 'revealed skill
relatedness' (RSR) method (Neffke and Svensson Henning 2009 22 ). RSR measures the
degree to which industries share similar skills requirements, and this is seen as a very
important vehicle for knowledge transfer between clusters (through people mobility). It is
based on a network analysis using data on job changes between industries, showing
proximity between industries in terms of skills sets.
Sophisticated analyses of clusters such as Henning et al. (2010) 23 combine this type of
analysis with a functional analysis linking economic structure with clusters challenges and
assessing the functions taken by the cluster initiative. The functions analysed are:
knowledge creation and knowledge diffusion; identification of opportunities and barriers;
stimulation of entrepreneurship/management of risk and uncertainty; market formation;
mobilisation of resources; legitimation. These types of analyses are conducted by experts
who are studying the cases in close cooperation with cluster actors: this helps taking into
account the innovation opportunities as identified by leading actors (companies,
universities, intermediaries, etc.). Mixing regional experts with international experts helps
to give more weight to the international competitiveness issue. Adding key stakeholders
from foreign clusters brings in a useful peer review dimension to the analysis.
4. Foresight: the aim of foresight is to capture existing expert intelligence sources on future
trends and make them accessible for present decision-making. The role of foresight is to
elucidate possible paths for the future in order to open the debate on possible development
paths. Foresight has the following characteristics 24 : Action-oriented; Open to alternative
futures; Participatory; and Multidisciplinary. There is a multiplicity of methods that can be
used and combined to implement foresight studies, the best known being the expert panels
and multi-round Delphi surveys: they differ with respect to their expected benefits,
conditions of use, time requirement, etc. Their common feature is that they rely heavily on
expert knowledge and involve interactions between experts (Table 1; see more details on
the FOREN website). For RIS3, foresight studies would ideally combine regional expertise
with international expertise able to put regional assets in perspective with wider trends.
22 Neffke, F. and M. Svensson Henning (2009), Skill-relatedness and firm diversification, Papers on Economics and
Evolution 0906. Jena Evolutionary Economics Group, Max Plank Institute of Economics.
23 Henning, M., J. Moodysson and M. Nilsson (2010), Innovation and Regional Transformation: from clusters to
new combinations, Region Skane.
24 European Commission (2001), FOREN Guide - Foresight for Regional Development Network - A Practical Guide
to Regional Foresight, IPTS Seville.
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