Abstract
Industrial districts and clusters are of utmost importance for economic growth and innovation in the European Union (EU). In this chapter, we analyse how smart specialisation policies have worked in different region types, combining cluster policies with smart specialisation ideas. Our study selects a sample of EU regions that differs strongly in terms of geography, size, socioeconomic dynamics, innovation capacities, and governance settings. Two key components of the strategy development phase deserved particular attention, that is, stakeholder inclusion and policy prioritisation. The cases selected are grouped into three main region types: advanced, intermediate, and less-developed regions. The empirical results suggest that advanced regions are in the best position to develop inclusive governance forms and to benefit from smart specialisation strategies. Intermediate regions also perform quite well with respect to the development of smart specialisation strategies, coping with stakeholder involvement, planning capabilities, and the capacity to prioritise a set of clusters and sectors. In contrast, in less-developed regions, weak innovation systems, insufficient experience with regionalised innovation policies, and high levels of state centralisation have undermined smart specialisation processes.
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- 1.
In this chapter we will consider the notion of industrial district as a synonymous of cluster. For a discussion of the differences and similarities, see Belussi (1996, 2015). It is clearly of foremost importance to distinguish between process of agglomeration (territorial concentration), clustering (specialised concentration interfirm linkages), and “distrectualisation” (historical specialised concentration showing social embeddedness). An analogous discussion has been presented also in Gordon and McCann (2000), where they classify agglomeration, clusters (localised interfirm transactions), and industrial districts (Italianate model of social integration). However, while in the first case local systems can evolve from one type to another (cluster ↔ district; district ↔ cluster), in the second case, we assume an “immanent”, “static”, and “unchangeable” typology based on social embeddedness characterises only the industrial district model (the Italianate model). In fact, what could be interesting to observe in the future is exactly the changing degree of cooperation, social benevolence, trust, and mutual support that is occurring within clusters and industrial districts in various cultural and economic contexts. This has clearly something to do with the evolution of industrial districts and clusters, path dependency, and look-in (Bergman 2007; Hassink 2010).
- 2.
- 3.
A similar approach can be found in Maskell and Kebir (2006), where all phases of development to describe specific cluster life cycle stages are compressed under the headline of “existence”, “extension” and “exhaustion”.
- 4.
“STI policies promote the ‘science-technology-innovation’ mode of generating novelty. STI policies are based on a narrow view of innovation and are typically supply-driven in nature, aiming to commercialise research results. DUI policies, in contrast, seek to foster ‚doing-using-interacting’ modes of innovation. DUI policies thus embrace a broader view on innovation. They are demand-driven policy approaches that aim to promote the development of new products to specific markets, interaction along value chains with customers and suppliers, specialised labour markets, local technical cultures, and so on (see, for instance, Isaksen and Nilsson 2013)” (Trippl et al. 2016: 118).
- 5.
The key findings and comparative analysis presented below draw on comprehensive and detailed reports prepared by the SmartSpec EU project (seventh framework program, grant agreement no: 320131) which has seen the cooperation of numerous universities including one external expert: Padua University (report on Basilicata), Cardiff University (Bremen, North East Romania, Slovenia), Charles University (Great Plain Region, Lodzkie, South Moravia), University of Groningen (Flanders, Limburg), Lund University (Scania, More and Romsdal), Orkestra (Murcia, Navarre), Newcastle University (Northern Ireland, Tampere), and Claire Nauwelaers (Provence-Alpes-Cote d’Azur).
- 6.
It is important to note that data presented in Table 3 refer to NUTS 2 for the reason of data availability. However, in some cases, we have selected smaller areas, covering NUTS 3 regions (Scania, Pirkanmaa-Tampere, More and Romsdal, South Moravia), or larger areas, and precisely, we refer only to one case where a country as a whole was chosen, which was in past a smaller part/region of Yugoslavia (Slovenia).
- 7.
More and Romsdal, which forms a subregion in Vestlandet, however, is classified as a moderate innovator.
- 8.
This classification is the outcome of several steps (see Trippl et al. 2016). In a first step, the regions have been divided into two large groups based on their rankings in the Regional Innovation Scoreboard 2014. A distinction was made between well-developed regions (innovation leaders and innovation followers, Scania, Tampere, Bremen, Navarre, PACA, Slovenia, Northern Ireland) and less-developed regions (moderate and modest innovators, More and Romsdal, Murcia, South Moravia, Basilicata, Lodzkie, Great Plain Region, North East Romania). However, a detailed analysis of challenges in relation to the development and implementation of S3 has revealed a need for regrouping. Slovenia has taken a national perspective on S3. The country is classified as follower in the Regional Innovation Scoreboard (2014). However, many of the S3 challenges found in Slovenia resemble those discovered in less-developed regions. More and Romsdal in Norway on the other hand is classified as moderate innovator. However, it is a wealthy region, performing well in DUI types of innovation, and it benefits from a vibrant entrepreneurship and collaboration culture. Thus, it faces very different challenges when compared to other regions that belong to the less-developed group. Navarre, Northern Ireland, and PACA are innovation followers. However, they face more severe challenges in relation to S3 than other well-developed regions. Thus, More and Romsdal, Navarre, PACA, and Northern Ireland form a separate group of regions which are more advanced than less developed ones, but their innovation systems are not as developed as of those in the well-developed regions group (Trippl et al. 2016: 120).
- 9.
In Bremen the establishment of the offshore wind industry cluster emerged out of the decline of the shipbuilding industry. It benefited from infrastructure in Bremerhaven and proximity to the North Sea. It started to grow faster in the last 5–7 years, though the project is already 12 years old. The regional government is currently investing €180 M in the Offshore Terminal Bremerhaven (dedicated to heavy load, assembly and transhipment facility for the offshore wind energy industry), to be completed by 2016.
- 10.
At present funding for three clusters has been announced, namely, materials, sustainable chemistry, and agro-food, although other clusters could be added in areas such as health and life sciences, logistics, and renewable energy systems. Each cluster will receive €500,000 per annum to come from public funds and €500,000 per annum to come from the private sector. They will be involved in a ‘cluster pact’ which is to be defined by the major firms and strategic partners involved in each cluster, such as higher education institutions.
- 11.
Seven clusters are mentioned in the smart specialisation strategy: ‘sustainable chemistry’, ‘specialised manufacturing solutions’, personalised cure and care, value-added logistics, specialised agro-food, integrated building-environment-energy cluster, and new ICT platforms.
- 12.
The South Netherlands region has identified three international top clusters which are already world-leading: agro-food and horticulture, high-tech systems and materials, and chemicals and materials. New clusters have been identified with international potential: life sciences and healthcare, bio-based activities, logistics, and maintenance.
- 13.
In Navarra several priority areas have been identified within the heading of cluster policies: healthcare economy (health services; medical appliances; biomedicine; service to persons), green economy (sustainable construction; sustainable vehicles; renewable energies; sustainable tourism; environment and waste), and talent economy (mechatronics; design and creativity; safety; business services; education). One can easily observe these regional targets which are too numerous and sometimes quite generic.
- 14.
The cluster programme had three specifications: the Arena programme for emerging clusters; the Norwegian Centre of Expertise projects for well-established clusters, supporting their export-oriented strategies; and the Global Centres of Expertise projects for leading clusters (selected on the evaluation of being global knowledge hubs within their sectors). iKuben is a cluster initiative for manufacturing firms under the umbrella of the Norwegian Arena programme. The majority of firms involved in smart specialisation are part of the maritime and the oil and gas sector; this cluster project aims to support platform technologies shared by all firms in logistics, new materials technology, and new technologies for product design. The Global Centre of Expertise ‘Blue Maritime’ supports the producers of marine equipment, shipyards, ship design companies, and ocean-going fishing vessels. Legasea belongs to the Arena clusters and supports research activities for exploiting marine biomass and alternative uses of raw marine materials. It includes companies operating for fishing fleets, land-based processing industries, fish farms, omega-3 manufacturers, and companies that refine marine proteins. The Arena cluster Norwegian Rooms support firms inserted in the furniture sector, promoting new design and new material technologies, marketing, branding, supply chain management, and internationalisation. The four cluster initiatives have developed strong technological platforms to promote regional and international networking.
- 15.
In Northern Ireland, the selected priorities are within five areas: (1) agri-food technologies (integrated value chain, traceability, niche/functional food, packaging, and marine cliff life), (2) sustainable energy (intelligent energy systems), (3) ICT (software engineering, big data/data analytics, cyber security, capital markets, digital content), (4) advanced manufacturing/materials (advanced engineering, electronics, and electrical components), and (5) life and health sciences (connected health and new areas in medicine). Enabling themes were leadership and cultural change, open innovation, public sector innovation, access to finance, and increase capacity and capability.
- 16.
Some regulative institutions set at the national level also appear to have a constraining effect on stakeholder involvement in the design of smart specialisation strategies. For example, in all the regions, reward systems in academia do not favour third task-related activities, providing few incentives for university researchers to participate in smart specialisation processes. Moreover, we found the existence of country-specific regulations hindering the implementation of the smart specialisation strategy such as a complex taxation system in Poland or the requirement of legal instruments in order to create collaborative spaces, such as science parks, in Romania.
- 17.
In Basilicata, the provisional priorities have included: aerospace (refers to earth observation sector), automotive, bio-economy, energy, cultural, and creative industry.
- 18.
This is, for instance, the case of the Great Plain Region, where current priorities in clusters/sectors selected included health industry (pharmaceuticals, medical devices, biotech, medical and health tourism, thermal water); food (functional food, innovative food, perspective food, dietary supplements); ICT (information communication technology) (innovative product development, technical information, future internet, security, enterprise management systems, big data, smart cities, e-business, software development, automation); electronics, manufacturing of machines; agriculture (crop production, manufacturing, precision agriculture); renewable energy (biomass, geothermal energy); and material sciences (electronics, photonics, nanotech, biomedical materials, solar panels, special materials, energy storage, energy product development).
- 19.
The smart specialisation strategy of Murcia grouped three thematic areas into agro-food (agriculture, livestock, fishery and food industry), quality of life (tourism, health, habitat), and driving forces (energy, shipbuilding, maritime, petrochemistry). The areas identified are related to the regional economic structure. However, the outcome of smart specialisation processes resembles a whole grouping of the regional economy rather than a process of prioritization. Furthermore, the areas that are identified do not have a common denominator. They include a sector-based group (agro-food), a theme group (quality of life), and a group based on its importance in the regional economy (driving forces). The focus of this strategy is blurred. The goals are very broad, and, in contrast, the problem of low education in the regional labour force remains unaddressed.
- 20.
In South Moravia the following areas have been prioritised: (1) advanced manufacturing and engineering technologies; (2) precision instruments; (3) development of software and hardware; (4) drugs, medical care, and diagnostics; and (5) and technologies for the aircraft industry.
- 21.
The final version of Slovenia’s smart specialisation strategy was based on nine priority areas: healthy working and living environment, smart cities and communities, smart buildings and home with wood chain, natural and traditional resources for the future, networks towards circular economy, sustainable food, sustainable tourism, industry 4.0 (factories for the future), health medicine, mobility, and materials as products. Prioritisation was not indicated.
- 22.
In the smart specialisation strategy for the Lodzkie region, six regional specialisation areas have been selected: modern textile and fashion industry, including design; advanced building materials; medicine, pharmacy, and cosmetics; power engineering, including renewables; innovative agriculture and food processing; and IT and telecommunications.
- 23.
However, in Northeast Romania cluster organisations are beginning to emerge, and there is the gradual development of science and technology park facilities in the main centre of Iasi. While there are very few high-technology companies, there are six active small clusters in the region in the fields of medical imaging, textiles, agro-food technologies, tourism, ICT, and new media. After prioritisation three areas were identified (agro-food, biotechnology, and clothing and textile).
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Professor Dr. Fiorenza Belussi and Michaela Trippl have received financial support from an EU research project funded under the FP7 grant number 320131, SMARTSPEC.
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Belussi, F., Trippl, M. (2018). Industrial Districts/Clusters and Smart Specialisation Policies. In: Belussi, F., Hervas-Oliver, JL. (eds) Agglomeration and Firm Performance. Advances in Spatial Science. Springer, Cham. https://doi.org/10.1007/978-3-319-90575-4_16
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