The operationalization of smart specialization policy has been rather limited because a coherent set of analytical tools to guide the policy directives remains elusive. We propose a policy framework around the concepts of relatedness and knowledge complexity. We show that diversifying into more complex technologies is attractive but difficult for European Union regions to accomplish. Regions can overcome this diversification dilemma by developing new complex technologies that build on local related capabilities. We use these findings to construct a policy framework for smart specialization that highlights the potential risks and rewards for regions of adopting competing diversification strategies.

The paper develops an evolutionary framework of regional resilience with a primary focus on the structural properties of local knowledge networks. After a presentation of the network-based rationales of growth and structuring of clusters, we analyze under which structural conditions a regional cluster can mix short run competitiveness without compromising long run resilience capabilities. We show that degree distribution (the level of hierarchy) and degree correlation (the level of structural homophily) of regional knowledge networks are suited properties for studying how clusters succeed in combining technological lock-in and regional lock-out. We propose a simple model of cluster structuring in order to highlight these properties, and discuss the results on a policy-oriented analysis. We conclude showing that policies for regional resilience fit better with ex ante regional diagnosis and targeted interventions on particular missing links, rather than ex post myopic applications of policies based on an unconditional increase of network relational density.

The paper develops an evolutionary framework of regional resilience with a primary focus on the structural properties of local knowledge networks. After a presentation of the network-based rationales of growth and structuring of clusters, we analyze under which structural conditions a regional cluster can mix short run competitiveness without compromising long run resilience capabilities. We show that degree distribution (the level of hierarchy) and degree correlation (the level of structural homophily) of regional knowledge networks are suited properties for studying how clusters succeed in combining technological lock-in and regional lock-out. We propose a simple model of cluster structuring in order to highlight these properties, and discuss the results on a policy-oriented analysis. We conclude showing that policies for regional resilience fit better with ex ante regional diagnosis and targeted interventions on particular missing links, rather than ex post myopic applications of policies based on an unconditional increase of network relational density.

No abstract

Smart specialization has become a hallmark of the EU's Cohesion Policy. Envisaged as a bottom-up initiative identifying local knowledge cores and associated competitive advantages, the operationalization of smart specialization has been rather limited, as a coherent set of analytical tools to guide the policy directives remains elusive. To tackle the weak underpinning of smart specialization policy, we propose a policy framework around the concepts of relatedness and knowledge complexity. We use EPO patent data to provide evidence on how EU regions develop new technologies in the period 1990-2009. We find that diversifying into more complex technologies is highly attractive but difficult for EU regions to accomplish. Regions can overcome this diversification dilemma by developing new complex technologies that build on local related capabilities. We use these findings to construct a policy framework for smart specialization that highlights the potential risks and rewards for regions of adopting competing diversification strategies. We show how potential costs of alternative strategies in regions may be assessed by making use of the relatedness concept, and how potential benefits of various smart specialization strategies can be derived from estimates of the complexity of technologies. A series of case-studies of different types of regions illustrate the utility of this policy framework.