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ABSTRACT
European guidelines for the smart specialization strategy (S3) required regions to identify synergies between technological domains within the same region (relatedness) and potential links of the chosen domains with other European regions (connectivity). The aim of this paper is to analyse if and to what extent regions have been able to implement such indications and the methodology adopted. The paper is based on a content analysis of the S3 documents approved by Italian regions. The empirical analysis reveals that only in a few cases regions considered relatedness and connectivity of technological domains. Moreover, the methods adopted by regions to detect potential links between the specialization domains is based more on anecdotal evidence than on the application of theoretically grounded methodologies. The paper suggests that the explanation for this omission is the absence of a consolidated methodology to deal with these issues and proposes some preliminary guidelines to overcome the problem.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. This is a new and challenging task for regional governments which are asked to change not only the content of their policies but also some consolidated routines in their definition and implementation (Kroll, Citation2015).
2. One of the general principles of the S3 (the four Cs) is ‘Connectivity and Clusters’, that is, ‘develop world class clusters and provide arenas for related variety/cross-sector links internally in the region and externally, which drive specialized technological diversification – match what you have with what the rest of the world has’ (Foray et al., Citation2012, p. 17).
3. Connectivity, that is, the presence of potential or actual relations between people and organizations, may be considered as a consequence of relatedness, which may refer to vertical relations (of the type implied by supplier–customer relations) or horizontal relations, based on similarities or complementarities in knowledge production and applications.
4. The RSR, suggested for intra-regional relatedness, is not valid in this case as job mobility takes place within limited geographical areas.
5. On this point, see also the discussion by Boschma (Citation2014).
6. NACE (Nomenclature statistique des Activités économiques dans la Communauté Européenne) is the classification of economic activities adopted in EU countries. It is based on the UN classification ISIS (International Standard Industrial Classification) and is similar to other classifications.
7. IPC is the classification adopted by the EPO (European Patent Office) and WIPO (World Intellectual Property Organization) to classify patents.
8. The NACE classification has 88 divisions at the two-digit level and 1342 categories at the five-digit level, which are the most widely used levels to define related and unrelated diversification.
9. This mapping has been attempted is some studies by relating NACE and IPC codes (Patel & Pavitt, Citation1997). At present, we do not dispose of reliable data linking sectors and technological domains.
10. In theory regions could use the associations between industries detected in other regions and countries, under the hypothesis that knowledge and skills required by technology are similar irrespective of the regions or counties in which they are applied.
11. Other regions specializing in the aerospace industry (such as Piedmont, Lazio, Lombardia, Puglia and Campania) have indicated in their documents the other Italian regions specializing in the same domain. This is because in 2009 the main regional clusters operating in the aerospace industry stated a collaboration process to set up a national cluster of the aerospace industry.
12. Campania follows the indication of the S3 guide to ‘matching what you have with what the rest of the world has’. In general, this kind of analysis is generically carried out as a SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis referring to overall region rather than specific specialization domains.
13. KETs are knowledge-intensive technologies that are likely to promote an advantage in the development of new products and services. EU identified the following KETs: Nanotechnologies, Advanced Materials, Micro- and nano-electronics, Photonics, Biotechnology and Advanced Manufacturing.
14. See Iacobucci and Guzzini (in press) for an analysis of this issue. An attempt to overcome this problem is being carried out in a research project at the Centre for Innovation and Entrepreneurship of Università Politecnica delle Marche by associating the technological fields indicated by Italian regions to IPC codes.
15. A previous analysis based on preliminary documents approved by EU regions revealed a similar situation also in other European countries (Iacobucci, Citation2014).