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.

There is consensus among scholars and policy makers that knowledge is one of the key drivers of long-run economic growth. It is also clear from the literature that not all knowledge has the same value. However, too often in economic geography and cognate fields we have been obsessed with counting knowledge inputs and outputs rather than assessing the quality of knowledge produced. In this article we measure the complexity of knowledge, we map the distribution and the evolution of knowledge complexity in US cities, and we explore how the spatial diffusion of knowledge is linked to complexity. Our knowledge complexity index rests on the bimodal network models of Hidalgo and Hausmann. Analysis is based on more than two million patent records from the US Patent and Trademark Office that identify the technological structure of US metropolitan areas in terms of the patent classes in which they are most active between 1975 and 2010. We find that knowledge complexity is unevenly distributed across the United States and that cities with the most complex technological structures are not necessarily those with the highest rates of patenting. Citation data indicate that more complex patents are less likely to be cited than less complex patents when citing and cited patents are located in different metropolitan areas.

Rigby D. L. Technological relatedness and knowledge space: entry and exit of US cities from patent classes, Regional Studies. US patent and citation data are used to measure technological relatedness between major patent classes in the United States Patent and Trademark Office (USPTO). The technological relatedness measures, constructed as the probability that a patent in class j will cite a patent in class i, form the links of a knowledge network. Changes in this knowledge network are examined from 1975 to 2005. Evolution of the patent knowledge base within US metropolitan areas is tracked by combining the knowledge network with annual patent data for each city. Entries and exits of cities from patent classes are linked to local and non-local measures of technological relatedness.

Evolutionary economic geography (EEG) indicates that regional industrial development is path dependent. The empirical studies in EEG however have not paid sufficient attention to the importance of global linkages nor the role of regional institutions in driving industrial dynamics. Based on firm level data of four-digit manufacturing industries during 1998 to 2008 in China, we find that Chinese regions branch into new industries technologically related to the existing industrial portfolio and related industries are less likely to exit. Further analysis reveals that global linkages, economic liberalization and state involvement not only create favourable conditions to allow a larger role of technological relatedness but also generate opportunities for Chinese regions to create new paths of industrial development.

Smart Specialisation was conceived as a ‘bottom-up’ framework to identify new growth paths connected to knowledge cores within regions. Although operationalization of Smart Specialisation has proven difficult, recent mappings of technologies in terms of technological relatedness and complexity suggest a useful cost–benefit framework. We extend these ideas, locating European Union cities in a Smart Specialisation space and tracking their development of technology since 1980. Results indicate that European Union cities with the largest gains in complex and related technologies enjoy an economic performance premium over cities with smaller gains in the complexity and relatedness of their knowledge bases.