Globalization, Modes of Innovation and Regional ...

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Globalization, Modes of Innovation and Regional Knowledge Diffusion Infrastructures Sverre Herstad

a b

& Thomas Brekke

b

a

Faculty of Economics and Social Sciences, Department of History, Sociology and Innovation b

Vestfold University College, Tonsberg, Norway

Version of record first published: 10 Sep 2012.

To cite this article: Sverre Herstad & Thomas Brekke (2012): Globalization, Modes of Innovation and Regional Knowledge Diffusion Infrastructures, European Planning Studies, DOI:10.1080/09654313.2012.713334 To link to this article: http://dx.doi.org/10.1080/09654313.2012.713334

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European Planning Studies, 2012, 1 – 23, iFirst article

Globalization, Modes of Innovation and Regional Knowledge Diffusion Infrastructures Downloaded by [Sverre Herstad] at 11:26 10 September 2012

SVERRE HERSTAD & THOMAS BREKKE Faculty of Economics and Social Sciences, Department of History, Sociology and Innovation, Vestfold University College, Tonsberg, Norway

(Received November 2010; accepted June 2011)

ABSTRACT Firms increasingly transcend the boundaries of regional innovation systems in their search for technology and complementary capabilities, and only rarely can they build their knowledge bases on science system output alone. Whereas the former decouple firms from regional user –producer networks, the latter raises important questions concerning the role of local science and education system actors in industrial development. By applying the “modes of innovation” concept on a Norwegian region, this paper discusses how science and education institutions can respond to the challenges of knowledge base complexity and globalization. It concludes that such institutions may play a vital role in supporting knowledge-based development, albeit different from that of academic knowledge exploration followed by linear technology transfer to industry.

Introduction The competitiveness of firms and regions in a globalizing economy rests on their ability to continuously develop, accumulate and exploit specialized knowledge assets. The development of such assets is contingent on the activities and networks maintained by individual firms (Giuliani & Bell, 2005), on the composition of the industrial structure (Boschma & Iammarino, 2009; Frenken et al., 2007) and on the presence and content of science and education institutions. As products, production processes and their underlying knowledge bases are becoming increasingly complex, individual firms are forced to draw on a wide range of component technologies and complementary capabilities (Duysters & Lokshin, 2011; Rothaermel et al., 2006) and combine leading scientific insights with specialized, experience-based knowledge (Bosch et al., 1999; Wang et al., 2009). As a result, innovation at the firm level is becoming embedded in global innovation networks (OECD, 2008; Trippl et al., 2009). This process appears to favour those regions which develop Correspondence Address: Sverre Herstad, Vestfold University College, Raveien 197, N-3184 Borre, Norway. Email: [email protected] ISSN 0965-4313 Print/ISSN 1469-5944 Online/12/000001–23 http://dx.doi.org/10.1080/09654313.2012.713334

# 2012 Taylor & Francis

Downloaded by [Sverre Herstad] at 11:26 10 September 2012

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S. Herstad & T. Brekke

information processing and knowledge absorption infrastructures (Simmie, 2003, 2004) able to link a set of technologically related albeit different, globalized actors (Giuliani & Bell, 2005; Graf, 2010) and industries (Lazaric et al., 2008). From globalization follows that it is becoming less relevant to understand clusters as sets of collaborating users and producers (Malmberg & Power, 2005). This in turn raises questions concerning the impact of cluster-building policies emphasizing the build-up of “strong tie” linkages between firms at the local level. From knowledge base complexity follows that the limitations inherent in development models based on advanced research linked to technology transfer schemes (Isaksen & Karlsen, 2010; Lester & Sotarauta, 2007) are becoming apparent. At the same time, the empirical landscape of industry and technology point to the enduring, even increasing, importance of regional untraded interdependencies (Storper, 1997), localized information and knowledge spillovers (Almeida & Kogut, 1999; Dahl & Pedersen, 2004), and thus regional innovation systems (Verspagen & Schoenmakers, 2000) broadly defined. This paper is motivated by the need for academic research to develop policy-relevant and action-oriented conceptualizations of regional innovation systems construction, in which globalization and knowledge base complexity is placed at the core. It analyses evolving processes of transformation and adaption occurring in a Norwegian region, as seen from the perspective of its two dominant industrial sectors. It shows how the technological landscape faced necessitates innovation behaviour that contradicts both traditional cluster theories and contemporary technology push reasoning. Yet, it also argues that new, and more important roles, are opened up. These involve the exploration of technological complementarities between the knowledge bases of different globally linked sectors, and thus construction and maintenance of knowledge-rich industrial environments larger than the sum of traded relationships contained within them.

Conceptual Framework Industrial Knowledge Development and Innovation Economists from Adam Smith and onwards have conceptualized development as a process which generate an ever-expanding range of differentiated products and technologies (Knell, 2008). As the stock of knowledge available for recombination diversify (Grossman & Helpman, 1991), the opportunities for new technology development exponentially grow. “What firms do” is therefore identification, coordination and integration of diverse external knowledge inputs (Kogut & Zander, 1996). These are identified through ongoing processes of innovation search. Intentional and unintentional exposure to information defines the “search spaces” of corporate enterprises (Katila & Ahuja, 2002). Evolutionary theorists (Nelson & Winter, 1982) have argued that the more diverse the search space is, the better are the effects of the alternatives selected. Empirical studies have found the impact of innovation search on subsequent technological evolution to be contingent on spanning organizational boundaries and product domains (Rosenkopf & Nerkar, 2001), and to be improving with the diversity of information sources used (Laursen & Salter, 2006). These studies find that the use of mature technologies from outside of own sector boundaries can provide as strong an impetuous to innovation as new technologies are developed by own sector (Katila, 2002), and argue that search should target knowledge domains characterized by a lack of shared experiences (Hargadon


Globalization and Modes of Innovation

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& Sutton, 1997; Majchrzak et al., 2004) rather than similarity. Due to the tacit and organizationally “sticky” (Asheim & Isaksen, 2002; von Hippel, 1994) nature of knowledge, and the complexity and uncertainty involved in much industrial development work, solving the search problem may open up issues of resource mobilization, knowledge transfer and interactive new knowledge development, i.e. a need for direct collaboration (Duysters & Lokshin, 2011; Tether & Tajar, 2008). The different actor groups with which collaborative relationships may form differ in what knowledge and problemsolving capabilities that may contribute, at what stage of the innovation process (Ebersberger & Herstad, 2011; Kessler et al., 2000; Roper et al., 2008). The successful identification of alternatives through search and transfer of knowledge through collaboration is dependent on the absorptive capacity of firms, i.e. their ability to identify, assimilate, transform and exploit external knowledge resources (Cohen & Levinthal, 1990; Zahra & George, 2002). This capacity is defined partly by the existence of prior related knowledge, which forms the basis for interpretation and transformation. It is also partly defined by the knowledge systems developed and institutionalized within the firm (Jensen et al., 2007; Lane & Lubatkin, 1998), which form the basis for attention allocation, communication and subsequent learning (Bosch et al., 1999; Ocasio, 1997). The knowledge systems that are maintained by firms represent institutionalized criteria for defining what relevant knowledge is, who are the legitimate participants to the process of organizational learning and which codes that are to be used when communicating internally and externally (Cowan et al., 2000; von Krogh & Grand, 2000; Lane & Lubatkin, 1998)—i.e. the dominant “mode” of learning and innovation (Jensen et al., 2007). The core of the “science – technology – innovation” (STI) mode is R&D departments of firms, linked to recruitment of highly skilled individual researchers, the use of academic communities and literature for search purposes and collaboration with science system actors. The outcome is explicit knowledge, which travels well, but requires adaption to contexts of application before it transforms into commercial innovation. The strength of the mode lies in its ability to draw on and push disciplinary frontiers, explore fundamentally new knowledge independent of specific contexts of application and provide the basis for radical innovations. This is also its Achilles heel; as transformation into large-scale industrial application often requires specialized complementary capabilities developed by other means than STI (Karlsen et al., 2011). This means that less “sticky” science-based knowledge is dependent on far more “sticky” specialized capabilities embedded in firms (DeSarbo et al., 2007; Laursen & Salter, 2004) and regions (Asheim & Isaksen, 2002; Isaksen & Karlsen, 2010). The core of the contrasting “doing –using – interacting” (DUI) mode is learning work organizations linked to external value chain actors in various forms. This model manages to mobilize and link experiencebased knowledge originating in different parts of the organization and value chain; thus ensuring that a stock of knowledge which is context-specific and application-oriented continuously evolves. This sustains an ongoing stream of incremental innovations along established technological development paths. For the same reason, it comes with the danger of lock-in. Thus, at both firm and regional levels it can be argued that sciencebased and experience-based knowledge are complementary (Milgrom & Roberts, 1995); in that, the full impact of either one on firm innovation or regional dynamics is dependent on the co-existence of the other. The activities of individual firms contribute information and knowledge spillovers into their surroundings, which then, depending on the diffusion capacity of the system as a


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whole (Lazaric et al., 2008), are made available for reuse and refinement by others. Because the process of specialization and diversification occur on an international scale, geographically bounded search, collaboration and knowledge transfers create a potential for lock-in (Narula, 2002) to diminishing return paths. The high cost of establishing extra-regional linkages may combine with the low marginal cost of continuing to use existing ones (Narula, 2002); causing actors to over-search local environments (Katila & Ahuja, 2002), which do not contain the technological novelties or complementary capabilities needed to sustain innovation-based industrial dynamics (Bathelt et al., 2004; Graf, 2010). Global network linkages (Coe et al., 2008) increases the exposure of individual firms to diverse information and knowledge, hence increasing both innovativeness and economic performance (Bellak, 2004; Frenz & Ietto-Gillies, 2007) at the firm level and creating a potential for richer regional spillovers (Balsvik, 2011; Graf, 2010). But it comes with less attention towards local collaborative linkages (Blanc & Sierra, 1999; Ebersberger & Herstad, 2012). A growing number of studies are, therefore, focusing on knowledge diffusion mechanisms that may remain in play under conditions of value chain globalization (Sturgeon, 2003). These point to the importance of labour market mobility (Ebersberger et al., 2011; Eriksson & Lindgren, 2009) and personal network formation (Agrawal et al., 2006; Dahl & Pedersen, 2004). Clusters of similar or related economic activities are found to be associated with particularly high degrees of labour mobility (Eriksson et al., 2008; Malmberg & Power, 2005); and by implication dense personal network formation. Firms also appear more able to absorb, transform and exploit (Bosch et al., 1999; Cohen & Levinthal, 1990; Zahra & George, 2002) diverse competencies if they are recruited locally (Boschma et al., 2009). Studies have also pointed to the importance of labour outflow from research-conducting (Maliranta et al., 2009) or multinational firms (Balsvik, 2011; Ebersberger et al., 2011) for innovation in firms which do not conduct R&D or are not themselves global players. Another important mechanism is spin-offs, i.e. the establishment of new firms to commercialize ideas originating in industry or research communities. These tend to cluster around their parent firms, and can provide a strong growth impetuous into the regional system. The existence and impact of within-region knowledge diffusion processes is intimately linked to the composition of the industrial structure, i.e. the set of firms between which knowledge can diffuse (Lazaric et al., 2008). “Agglomeration economies” (Beaudry & Schiffauerova, 2009) arise from a high degree of regional specialization, and the formation of a thick and highly specialized labour market, a common supplier infrastructure and a common research infrastructure upon which technologically similar firms may draw. Cognitive proximity—similarity of activities—combined with co-localization is said to foster trust conducive to information-sharing and collaboration, and enable local spillovers to diffuse and be absorbed with little friction. However, homogeneity substantially reduces the likelihood that the knowledge present may form combinations which are truly novel, and increases the likelihood of negative technological lock-in. It also comes with the risk of competition between firms operating in similar markets; and of exogenous business cycle shocks upon the cluster as a whole, rather than individual firms. Others have, therefore, argued that diversity rather than specialization in the regional industrial structure is more conducive to knowledge diffusion and innovation. Diversity provides the basis for knowledge diffusion between technologically different activities, and hence for the so-called “urbanization economies”. Diversity is assumed to “ . . . facilitate


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more radical innovation as knowledge and technologies from different sectors are recombined, leading to completely new products or technologies” (Frenken et al., 2007, pp. 6 – 8). But diversity comes with the risk of fragmentation (To¨dtling & Trippl, 2005) caused by cognitive distance (Nooteboom, 2000). Regional diffusion mechanisms are, therefore, needed to bridge cognitive distances and accelerate processes of reconfiguration in the intersection between diverse competencies already present (Cooke, 2007, 2008; Lazaric et al., 2008; Simmie, 2003).


Constructed Knowledge Diffusion Infrastructures This underlines the importance of regional knowledge development, accumulation and diffusion infrastructures which operate independently of local inter-firm collaborative linkages and labour markets, because such may explore technological relatedness across (i) different sectors and clusters, which form different labour market segments; and across (ii) different nodes of global innovation networks (Owen-Smith & Powell, 2004). Examples include regional business and technology councils, regional development organizations and different labour training and mobility schemes. However, these are also mechanisms which are often (a) dependent on the commitment of leading industrial actors to be combined with the successful definition of common interests and objectives among a broader range of firms; making them vulnerable to fluctuations in such commitment; and/or (b) attempting to build, or even presupposing, commitment to local “collaboration” which is contradictory to individual actor needs for attention to be directed outwards (Cotic-Svetina et al., 2008). In addition, they may (c) experience problems in adapting to circumstances which evolve with structural change, even when this structural change can be attributed to the initial effectiveness of the infrastructure itself. Universities, university colleges and research institutes may, therefore, play an important role because they constitute stable, third-party actors which can operate independent of individual firm or sector preferences, yet adapt teaching and research to collective regional potentials and demands (Chatterton & Goddard, 2000). They can help to integrate previously separated areas of technological activity and thereby unlock and redirect knowledge that is already located in the region, but not put into its full productive use (Lester & Sotarauta, 2007). The core contribution by the university is, therefore, still education, and the creation of a public space for ongoing local conversation about the future of technologies and market. Universities may accumulate research-based knowledge from a broad spectre of places (regional, national and international) and industrial sectors, and thereby serve both as gatekeepers (by linking knowledge from outside to learning processes within, see, e.g. Graf, 2010) to the regional system and as knowledge banks (by externalizing and accumulating knowledge at the intersection between different industrial activities) within them. This presupposes that universities and university colleges position themselves to play a different role than that of technology production at arm’s length from industry: they must interact with and learn from industrial actors (Becher & Parry, 2005), in order to align with and diffuse knowledge between them. Consistent with this, a growing number of empirical studies (Balconi & Laboranti, 2006; Bekkers & Bodas Freitas, 2008; Daraio & Bonaccorsi, 2007; Kaufmann & To¨dtling, 2001; Ponds et al., 2010; Varga, 2009) have shown that collaboration and interaction

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between the university and the industry is a highly beneficial and cost-effective way to develop and commercialize new knowledge and technology (Etzkowitz et al., 2000). Yet, these studies have also shown how the relationship between industry and universities is structured by the specific knowledge conditions involved (Bekkers & Bodas Freitas, 2008; Ponds et al., 2010), and consequently that the knowledge production and diffusion role of the university cannot be understood independently of such specific local circumstances.


Innovation System Dynamics in Context The Vestfold region is hosting a set of specialized and highly internationalized firms within electronic- and microelectronic manufacturing (Asheim & Isaksen, 2002; Onsager et al., 2007) and maritime engineering. It is located on the Western shores of the Oslofjord, approximately 1-hour travel from the capital city of Oslo. In electronics, the firms which eventually would become core actors were all established from the 1960s through to the early 1980s, and combined external science-based knowledge with pre-existing industrial competences and capabilities originating in, e.g. maritime radio production. This occurred as a process of “cluster mutation” (Cooke, 2008) which during the 1980s and early 1990s entailed diversification into areas such as sensor technology, ultrasound technology and advanced communication equipment. Throughout this process of growth and diversification, firms continued to draw on research communities located outside the region, while contributing to the build-up of a specialized knowledge base within it. This has included various network initiatives. At present, the Electronic Coast (EC) network consists of a stable population of 36 member firms, which operate in diverse international markets. Few of these are in direct competition with each other, and most are now embedded in their individual global production and innovation networks. The maritime engineering industry is completely dominated by six large companies which operate in segments such as oil and gas subsea construction. The evolution of this industry in the region bear similarities to the evolution of the electronics cluster, in that it has entailed the consolidation and transformation of pre-existing regional shipbuilding activities and competences by means of scientific inputs and market drivers originating outside the cluster itself, i.e. the strong Norwegian national innovation system in this field (Isaksen, 2009). These companies only recently formed the Engineering Coast collaborative network, largely as a result of pressure exerted through regional development work. They have historically enjoyed denser linkages to the Vestfold University College (VUC) and much stronger support from its educational programmes; from which related activities such as vessel simulator development and crew training programmes anchored at the VUC have grown. The late entry into a formalized regional collaborative network can partly be attributed to the dominance of large firms with strong internal capacities, and partly to the fact that they compete on the same labour and product markets.

Methodology The empirical analysis is based on interviews with managing directors and R&D executives in 11 firms, conducted in two rounds. The first explorative round covered three of



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the largest actors of the electronics cluster, and focused on issues spanning from overall competence upgrading to the organization of specific innovation projects. Based directly on these interviews, a survey questionnaire was developed and sent to the 42-member-firms of the EC and Engineering Coast networks. The questionnaire obtained information on key innovation activities, notably R&D investments, information sources and collaboration partners used in the innovation process. In addition, it contained a separate set of questions capturing the importance of different competence upgrading mechanisms. As we explain in detail below, this information was used to group firms according to their dominant “mode” (Jensen et al., 2007) of knowledge development. All sampled companies were contacted prior to electronic distribution of the survey. Of the 31 responses received from R&D managers and managing directors, 28 where complete and used in the subsequent analysis. This is equal to a response rate of 67%. Nine additional case studies were then conducted to ensure a case study sample which covered both clusters, each of the different modes of knowledge development at play in these clusters and the range of firm sizes involved (see Table 2). Interviews conducted in this round used survey findings as the point of departure, and were discussed indepth with respondents. Consequently, the empirical analysis uses qualitative evidence to interpreted and explain the broader picture portrayed by survey evidence. In addition, the analysis draw on a total of 12 interviews with personnel at the VUC, numerous informal conversations and the use of material, documenting relevant internal strategy processes from late 1990s until present. VUC respondents include the Headmaster and University Director, the Dean at the Faculty of Technology, as well as managers and academic staff at the Department of Micro- and Nanotechnology, Department of Technology and Department of Maritime Studies. As both authors are employees of the VUC, informal discussions have been numerous and have provided important contextual information. Industrial Knowledge Development and Networking We first consider the nature of the knowledge bases upon which firms build their activities (Asheim & Coenen, 2005), and how these are reflected in their knowledge development and innovation activities. In order to approach this systematically, we draw on survey information, indicating the importance of different competence upgrading mechanisms. This information is used to construct a set of indicators which describe the importance of competence upgrading by means of DUI and STI, respectively, (Jensen et al., 2007). The overall assumption is that the different informal competence upgrading mechanisms specified by the survey (daily work, teamwork, and customer and supplier interaction independently of innovation collaboration) all capture different aspects of competence upgrading by DUI; whereas formal mechanisms such as internal R&D and interaction with universities and research institutes capture different aspects of competence upgrading by means of STI (see, e.g. Asheim et al., 2012). The value of the resulting indicators is the average importance of items entered, and can vary between 4 (not used/relevant) to 1 (highly important). This is described in Table 1, which also includes the sample value ranges and means. To investigate the assumption that each item entered capture a certain aspect of the same latent construct (i.e. the underlying mode at play), we have calculated reliability scores. The value of Cronbach’s alpha approaches the maximum value of 1 the higher the number of items that are entered, the

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Table 1.

Indicator system

Indicator construction, reliability scores and descriptive statistics DUI mode composite indicator Items entered: 1 (high importance) to 4 (not used) Stated importance (1 high to 4 not used) of: Competence upgrading through daily work Competence upgrading through teamwork Competence upgrading through customer interaction Competence upgrading through supplier interaction Reliability (Cronbach’s alpha) 0.8 Sample range 1–2.8 Sample mean 1.6 STI mode composite indicator Items entered: 1 (high importance) to 4 (not used) Stated importance (1 high to 4 not used) of: Competence upgrading through R&D Competence upgrading through university interaction Competence upgrading through research institute interaction Reliability (Cronbach’s alpha) 0.7 Sample range 1–3 Sample mean 2.0

Table 2.

Survey and case study firms by sector and mode Combined mode

Survey sample Electronics 14 Engineering 3 Survey sample mean indicator scores DUI mode 1.5 STI mode 1.7 N (survey) 17 Case study sample Electronics 3 Engineering 3 N (case studies) 6

STI mode

DUI mode

Total

2 1

6 2

22 6

2.5 1.8 3

1.4 2.9 8

2.0 1.6 28

1 0 1

2 2 4

6 5 11

stronger are the correlations between these items. Although this is somewhat contingent on the number of items entered, a score of 0.7 or higher is normally interpreted as indicating that a composite indicator capture a latent construct (Nunnally, 1978). Both indicators meet this requirement. We have then grouped observations according to their dominant mode of knowledge development. This is done through a hierarchical cluster analysis with a three-cluster solution specified, using the normalized DUI and STI indicator scores as input variables. As previous studies (Jensen et al., 2007), we find distinct STI and DUI groups, in addition to a large intermediate group of companies which score high on both indicators (see, e.g. Isaksen & Karlsen, 2011). Basic descriptive statistics on these clusters, including cluster mean scores on the different input variables, are given in Table 2. For each survey sample group, we have calculated the average R&D intensity (R&D investments as percentage of sales), and the percentage of this R&D which target different

Globalization and Modes of Innovation Table 3.


Combined (N ¼ 17) STI (N ¼ 3) DUI (N ¼ 8) Total (N ¼ 28)

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R&D investments by mode of innovation

R&D intensity

Orientation of R&D (average shares of R&D conducted by target area)

Average share of sales

Customer needs

Refinement of existing technologies

New product development

Longterm research

24.7 46.8 6.3 23.3

28.8 5 53.6 29.9

37.8 28.8 35.0 35.8

24.4 45.0 24.4 27.7

9.0 21.3 0 9.2

specified activities. The results are given in Table 3. This provides us with a point of departure for understanding not only the interdependencies between different competence upgrading activities which combine to form distinct modes; but also how these mirror different R&D strategies and differences in the overall market and technology context faced by the different groups (see, e.g. Leiponen & Drejer, 2007; Malerba & Orsenigo, 1993; Marsili & Verspagen, 2002). In the group of eight companies which state that competence upgrading occur primarily through daily, team-oriented work processes and interaction with customers and suppliers, R&D investments are limited. Those conducted predominantly target specific customer needs and the refinement of existing technologies (see Table 3). Six of these are electronics manufacturers; producing either specialized components or delivering manufacturing, test system and logistics services to system integrators. Two are large maritime engineering and service providers; and all but one are affiliated with multinational corporate groups headquartered in Vestfold or in the neighbouring Kongsberg region of Norway. Innovation search patterns are strongly oriented towards the mobilization of ideas and information already existing within the own organization and parent group network; and external search and collaboration patterns reveal the overwhelming importance of client firms— located elsewhere in Norway or abroad. Continuous, complex and context-specific problem-solving characterize their innovation activities. Subsequent discussions of survey findings with firms reveal that inputs from more systematic knowledge development processes enter indirectly, through customer and supplier linkages. For instance, subsea engineering firms are heavily dependent on interaction with leading subsea system designers, who in turn collaborate intimately with specialized Norwegian research communities. They are also dependent on collaboration with certification agencies, which provide quality and compliance control on behalf of authorities and customers. Competence upgrading by means of external recruitment is considered of relatively low importance, and interviewed firms reveal that this is due to general supply deficits combined with firm specificity of knowledge involved (DeSarbo et al., 2007; Wang et al., 2009). The latter translate into requirements of firm-specific training, and reinforce the reluctance towards hiring new staff which is already present within electronics due to a slow overall market growth. A respondent elaborate: I have people here who had only vocational training when they started. Yet, they are just as important to us as many of our highly qualified engineers, because they

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possess all these competence you only gain through experience. These kind of competences are really difficult to find anywhere else than here. The mirror image of this is found in a very small group of companies which state that core competencies are developed primarily by means of systematic R&D, linked to external science system actors; and that learning through daily, team-oriented work processes contribute very little if anything to building these competencies. Only three firms constitute this group. They are found within advanced subsea engineering (established by another engineering incumbent), in the interface between electronics and life sciences, and in the development and production of optics and display technologies. The predominance of the STI mode should not be confused with young age, as all have been in operation for at least 10 years. Both customers and suppliers are present as information sources and collaboration partners in specific innovation projects; and are considered important in this role. Yet, no single company in this group state that customer collaboration is of high importance to competence upgrading, and external search and collaboration is distinctively oriented towards the science system. Reflecting this orientation is large investments in long-term basic research and the development of new technologies. The external orientation towards science is reflected in an internal competence base which is dominated by personnel with education at the PhD and master levels. External recruitment is an important mechanism for upgrading these knowledge bases, which are strongly measured by formal qualifications. The one firm study we have been able to conduct within this group confirms our expectations of weakly developed firm-specific components of the knowledge base. DUI and STI mode companies are opposite extremes surrounding a larger group of companies in which competence evolve by means of daily, team-oriented work linked to external customer and supplier interactions; combined with systematic R&D linked to science system interfacing. They are either system integrators who deliver complete product systems to demanding final end uses at, e.g. hospitals, airports or vessels; or component manufacturers which operate in markets such as aerospace, medical and subsea. They share the DUI focus on external customer search and collaboration, and draw heavily on their internal stocks of accumulated daily work and R&D-based experiences. The existence of an R&D-based knowledge stock is visible in the form of a much higher R&D intensity than within the DUI group. Yet, the distribution of this R&D across different research activities is much more even than within the STI group. Combined mode firms are also distinctively less oriented towards the science system than customer search, and both long-term research and more short-term product development is to a substantial degree shaped by existing or expected customer needs. As explained by a leading electronics firm, this form of combined knowledge development is particularly demanding: . . . it takes years before your average engineering can be of real use in product development. For instance, it is often impossible to do product development without also developing new tools and processes. So a range of different engineering and technical skills become involved. This does not entail that it becomes less academically or intellectually demanding—it just becomes much more complex. We bleed when experienced engineers decides to leave us.



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“Strong tie” innovation collaboration result from prior search, can be governed contractually (Adams, 2002) and span geographical boundaries. The overwhelmingly most important collaboration partner group to DUI and combined mode firms is the customer—predominantly found outside the region (e.g. in the automotive and aviation industries of continental Europe and the US)—while parent group resources are stated as relatively unimportant to this group. For combined mode firms, the median survey value for innovation collaboration with the VUC is “unimportant”, whereas the median value for collaboration with science system actors outside the region is “important”. When we add to this the low importance of the VUC collaboration stated by DUI firms, questions arise concerning the extent to which the university college play other roles which are not captured through a singular focus on innovation collaboration and contract R&D. A clear indication of the answer is as to how the region remains important as a venue for those processes which resist formalization, planning and codification, i.e. competence upgrading independent of specific innovation projects. For instance, whereas 9 out of 17 combined mode firms state that localized information flows are important for overall “competence upgrading”; only two such firms state that this search channel is important to “innovation”. At the same time, most firms in this group state that international information flows specific to their sectors as moderately or very important to “innovation”. Only firms in the DUI group are heavily oriented towards the use of localized information flows as inputs to innovation; while combining this with orientation towards global sectorspecific communities in a manner similar to that of the combined group. As put by a contract manufacturer: The value added is in how we can draw on the advanced production competences in the region—this makes us more flexible and able to deliver far more stable quality even for small series—and in how we build complementary services around our production activity. But obviously, we need to keep track of what goes on internationally. What are competitors doing? What are machine tool developers doing? What do customers really want? It’s a continuous stream of critical information, which we have to tap into and select from. The “dual” global – local search and collaboration linkages maintained by combined group suggest that they serve as gatekeepers which link the VUC, and thus the region as a whole, to external sources of information it would not otherwise be able to access (Ebersberger & Herstad, 2012; Graf, 2010). As one of the VUC respondents exemplify: Collaboration with (three anonymous electronics firms) is something special. These companies have a good overview of leading research communities in Europe and other places. We direct get access to their connection. Yet, from the firm perspective, neither search nor collaboration involving the VUC is about access to cutting-edge technology and research facilities. As one of the firms mentioned by the VUC respondent above elaborates: . . . we don’t expect to find leading technology at VUC, to put it that way. The educational bit is important, but there’s something else to it, which is difficult to

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S. Herstad & T. Brekke explain—difficult to put into words. It has to do with it serving as some kind of focal point to us, collectively. It is much more bout building an environment.


An important difference between engineering and electronics is how the former in essence function as a regionalized segment of a larger national innovation system (see, e.g. Isaksen, 2009), which is specialized in this technological field. It includes Norwegian Technical University in Trondheim, with its dense linkages to most major maritime and offshore oil and gas players in Norway as a whole. This is reflected in a much longer tradition for engineering education at the VUC—supportive of engineering firms and supported by large-scale national level research, education and industrial innovation within this field in Norway. As explained by one of the large engineering actors: Having an engineering education here which is linked to an industrial base is important because it attracts students, and strengthens the local labor market. And it contributes to maintain our linkages towards VUC, which in the long run is beneficial to environment as a whole. We are global players in need of a regional anchoring point. But technology . . . in our case, we collaborate a lot with clients, most of what we do is contingent on what is new on the system side, and what is driven by requirements of new deepwater fields. The Trondheim (Norwegian Technical University) environment and the large operating companies are setting the stage on the technology side. We make it possible in practice. The Changing Regional Knowledge Diffusion Infrastructure The overall picture portrayed by the case studies is, therefore, one in which (a) scientific knowledge only constitute one of many components entering into firm innovation, and (b) these various components to a large extent are sourced outside a region which (c) predominantly serve as a platform for competence maintenance, and—to a more limited extent—information “buzz” (Storper & Venables, 2004) and search. This has resulted in a strain on knowledge diffusion mechanisms built on the assumption that direct collaboration and coordination between firms is a necessary prerequisite for regional industrial dynamics. They include mechanisms such as the Avanse and EC networks, and the more recent Engineering Coast initiative. The Avanse network has traditionally served an important function by enabling exchanges of skilled production personnel between firms within the electronics cluster, and reallocation of personnel in cases of redundancy. The importance of this role has diminished with the overall downsizing of local production. In 1998, the VUC led the formalization of the EC project, supported by the public regional development programme. This originally started as an informal network of local business managers working at electronic- and microelectronic companies. The re-vitalized EC-network was to form the basis for entrepreneurship and new firm formation, and was anchored and organized as a broad participative process, involving a range of regional stakeholders (Finsrud, 2007). Yet, it has not been successful in nurturing new-firm formation. Already by the late 1990s, several electronics companies pointed to the well-developed interplay between the VUC and maritime companies, and expressed dissatisfaction with the lack of more substantial commitment to electronics. The university college had built advanced courses not only within maritime engineering, but also within related service


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areas such as logistics and the crew simulator training. At the same time, teaching and research within fields relevant to the electronics industry was outdated and not adapted to advanced industry needs. Leading system developers and original equipment manufacturers pointed out that long-term, high-risk investment in complex internal R&D was financially difficult to combine with the need for broader investments in the firm-specific competences of their staff. Something had to be taken out of this equation, and the latter was the most obvious choice. As put by a large electronics firm:


Educational programs at VUC where completely irrelevant. We need highly specialized competences and what they do in Trondheim (Norwegian Technical University) is not really what we are looking for. Hence it was impossible for us to find relevant competences by other means than poaching from other firms, hiring when somebody had to downsize, or build it ourselves. The VUC responded from the beginning of 2000, following the election of a new principal and new faculty deans. The Faculty of Social Sciences developed a tailor made management educational programme, aiming at improving both management practices and co-operation within the industrial environment. The programme was designed for the specific purpose of allowing participants to share their work experience, and thus drew its content out of these experiences. In 2003, the VUC decided to establish a new master programme in MEMS (nano- and micro-electro-mechanical systems) engineering. However, the VUC had almost no experience of managing such an advanced and expensive master programme, nor the technological competences to enter into it. To get a master programme officially certified and considered relevant to industry, the VUC needed to obtain the necessary specialized competences; and invest in expensive supportive infrastructure such as clean room laboratory and production equipment. The VUC, therefore, made an agreement with large, leading electronics companies. These were willing to share their technical expertise as tenant professors, and to donate necessary research equipment to the university college (Nilsson, 2006). The VUC also recruited from local companies (professors, PhDs and technical assistants). This enabled the university college to build a foundation for collaborative research, involving industry partners, and eventually the competences necessary for more self-sufficient activity within the specific field of MEMS. As put by a former industry, now a VUC employee: Research collaboration between us and VUC was essential for the build-up of competences here (i.e. at VUC) during the early phases. And one of the problems was funding. University colleges have little research funding to begin with, and there’s not much out there relevant for this kind of activity. Their main role is supposed to be teaching, but what about the content? It has to come from somewhere, and be relevant for something. What we do can’t be learned simply by reading about it. At the university college side, the process created internal tensions because it entailed the channelling of attention and financial resources towards one specific area, at the expense of others. In practice, this meant a substantial reorganization of the engineering department, and downsizing of established academic strongholds. At the industry side, the content of the programme was considered critical because it would, by means of


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labour supply, directly contribute to defining the future “platform” technology for the cluster as a whole. MEMS technology was chosen largely as a result of pressure from leading firms already operating in this field; and able to supply the VUC with the necessary competences. It was legitimized with reference to this being a general purpose technology applicable—and increasingly relevant—across most segments of advanced electronics. It is also a technological field with potential for drawing heavily on other high-velocity fields, such as biotech. Others still claim that a stronger emphasis on the “packaging” of advanced electronic components would have better reflected the breadth of activity in the region; contributed more to maintain production capacity and thus competences in the region—consequently providing a broader platform for regional development. The Faculty of Science and Engineering eventually became more attractive as a partner in several large-scale joint research programmes, such as NEWPACK1 and MULTIMEMS,2 run by staff member from the University College in partnership with the local industry and the national research institute SINTEF. External founding related to such collaboration with industry, and the knowledge transfer into the VUC which came with them, enabled the Faculty of Science and Engineering to build a new institute with a bachelor and master degree programme in MEMS technology. The subsequent establishment of a National Centre of Expertise (NCE) in MEMS engineering marked a shift towards a more active role for the VUC as a MEMS technology “developer”. This institute now has 30 employees, hosts 25 PhDs and is in the process of applying for certification of its own PhD programme. The more self-sufficient research role has led to a shift in its approach to commercialization. In 2008, the NCE partnership revived Microtech Innovation (MTI), established in 2003 by the local government and three leading industrial firms to serve as a commercialization vehicle. MTI is now to serve not only as the main commercialization engine for NCE and VUC technology, but also as a national innovation and commercialization player with extended arms into the MEMS research communities in Oslo and Trondheim. As of 2010, MTI incorporates the networking organization EC. In addition, management responsibility for the MEMS Centre of Expertise has been transferred from VUC to MTI. This represents an explicitly stated reorientation of attention away from serving the existing industrial base, and has come at a cost. As explained by one of the combined mode firms during one of the interviews: We considered moving into the new innovation centre they are building, but decided not to. We think the game there has changed, and are worried that this may draw attention towards other activities which, frankly, are not our concern. We don’t really want our people running around on a daily basis discussing all sorts of things with students and VUC researchers, and risk that they jump ship. They are far too valuable for us. The role of the VUC as a contract research partner for the electronics industry is also relatively limited due to difficulties in defining development work which can be conducted in isolation from the increasingly complex knowledge bases of firm (see, e.g. Ebersberger & Herstad, 2011; Grimpe & Kaiser, 2010; Teece, 1988; Weigelt, 2009 for discussions of contract R&D). Contract R&D is perceived to involve large resources spent on communicating tacit, contextual knowledge to the VUC researchers and students (Fey & Birkin-


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shaw, 2005), which is not covered by formal intellectual property right measures (IPR) measures and difficult to regulate contractually. The R&D manager of an advanced component manufacturer explains:


We need to focus on international research projects, our most important users and what is cutting edge technology in our field. Some contract work at VUC is fine, given that it can be done in isolation from other internal processes and competences. But we cannot spend time explaining all sorts of contextual things to students and VUC researchers, particularly not to students who are not formally employed at VUC, in the process risking that it leaks out. This stuff we must do ourselves, or with other partners than VUC. This growing reluctance among established firms towards knowledge exchanges, involving the VUC is reinforcing the emphasis put by the latter on nurturing new firm formation. Yet, after Sensonor established MEMSCAP in 2000, there have been few signs of new firm formation “within” electronics based on competences “on” electronics. Part of this is again directly attributed to the complexity of technologies involved, the need to build “organizations” which develop and accumulate complementary capabilities (Herstad, 2011) by means of DUI-based processes and thus the need for committed, long-term financing (Audretsch & Weigand, 2005; Isaksen & Karlsen, 2010). As explained by a VUC researcher and former industry employee: Look at how long it took (anonymous microelectronics firm) to be able to stand on their own feet. This is not something for your average venture capitalist, and it is difficult, even impossible, to imagine that entrepreneurs themselves even consider carrying these investments, as many of the pioneers tried to do. Of course, it is commonly known how they have struggled—and even struggle still. I think the more advanced commercialization stage, rather than the research as such, will prove to be main bottleneck to industrial development within electronics, irrespective of what we now have built up at VUC. This we have to come up with a solution to. Similar reluctances are found among researchers at the VUC, who consider this type of contract research to be not only demanding, but also problematic from an academic point of view. As explained by a VUC researcher: Eventually we decided to place greater emphasis on doctoral education than contract research, due to the difficulties we experience when trying to enter into and understand corporate development work. We do not have the capacity to participate in such time-consuming processes. And we are continuously being squeezed by other research institutions. As suggested by the theoretical discussion, DUI firms emerge as locked into their established technological development paths, whereas STI firms struggle with transforming research into viable commercial activity. Whereas the latter point towards the importance of committed, competent capital and thus is outside the realm of the VUC influence, one could argue that an important contribution from the VUC would be to link DUI firms more densely to science-based knowledge, contribute to raising internal research capacity and

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transform them into combined mode actors able to enter new technological development paths. This is clearly acknowledged by leading DUI firms within electronics.


We feel we have an important role to play, but they (VUC) don’t seem to be interested in the kind of stuff we do. But think about it—the objective of what they do should not so much be research in the field of nanotechnology as such, but new commercial activity here in Vestfold based on it. And what would you need then? The kind of competences on packaging and advanced, small-scale production we can offer. But at the moment we’re just not a part of it. Exercising this role appears to be at odds with the stronger emphasis on research excellence which has followed in the wake of increasing self-sufficiency in the MEMS area at the VUC, because DUI group firms are considered those representing the lowest potential for academic value-added on the side of the VUC. A VUC respondent explains: We used to be in a situation where we had to say yes to everything industry wanted us to participate in. Now we can assess what is academically interesting or not . . . . It is more interesting and easier for us to collaborate with other universities through joint projects and publication work. With respect to cluster-building within engineering, the point of departure for the recent Engineering Coast network initiative was quite different from the situation within electronics at the turn of the century. The VUC has a long tradition for collaborating with engineering firms; internal competences which mirror this and external linkages to world-leading universities and research institutes which serve as the basis for a strong focus on education programmes and simulator training. The large multinational enterprises who dominate this cluster build on experience-based knowledge accumulated in the region through decades of shipbuilding and offshore engineering activities, maintained and refined by the VUC educational programmes developed in dense interaction with industry. Yet, again we find innovation collaboration to be dominated by external linkages to customers and specialized research environments elsewhere in Norway, and abroad. New firm formation remains rare not only within the regional cluster, but in the industry as a whole due to its reliance on combined STI and DUI processes with resulting high levels of cumulativeness (Malerba & Orsenigo, 1993) at the level of the firm. When it occurs, it, therefore, tends to take the form of industry spin-offs rather than academic spin-offs. And when the latter does occur, it tends to do so around the technologically leading university and research institutes in Trondheim, Mid-Norway. The establishment of the Engineering Coast network has arguably had the effect of building identity, and of revitalizing the VUC interest in this particular sector. Yet, it has problems defining roles which extend beyond ensuring VUC awareness to industry needs and incremental changes in established education programmes. Consequently, the VUC is left with a role where education programmes targeting the respective industry clusters is the main support provided to these—and where the actual impact of these education programmes on regional development more broadly, while clearly important to existing firms, is limited by the lack of employment growth (electronics) and new firm formation (electronics & engineering) within the respective clusters—largely due to factors which will remain outside the realm of the VUC influence.


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Beyond Technology Transfer and Individual Cluster Support It is our contention that excessive emphasis on the role played or not played “within” individual industry clusters, in support of individual firms and new firm formation within them, misses the potential for knowledge-based regional development based on related variety and cluster mutation (Cooke, 2008) processes. The build-up of activity in the MEMS field at the VUC, combined with a revitalization of engineering activities in the wake of Engineering Coast network formation and identity building, has (i) boosted third-partly (i.e. VUC) exploration of these two knowledge fields, (ii) made the resulting knowledge available to firms independently of collaborative interaction with those firms in which they were originally contained; and (iii) increased the regional supply of basic competences in these fields not only through increased output into the regional labour market, but also by means of strengthened gravitational pull within the Norwegian labour market as a whole. The fact that both surveyed and interviewed firms do not see the VUC as a vital partner to “their” future innovation processes point not to the irrelevance of the university college in knowledge-based regional development, but rather to the importance of exploring the potential for cluster mutation. As explained by a former industry researcher, now a VUC employee: Participating in cluster activities gives me access to insight I would otherwise not have had, and I use the opportunity to talk about what we are working on and how it can be applied in different contexts. In this way we may connect businesses that do not have experience with micro-technology, but need this expertise, together with micro-technology companies. Examples are still anecdotal, and it is surprising to see that the interface between engineering and MEMS remain less explored within the VUC than—at least historically—by industry itself; e.g. in the form of the advanced naval control systems which formed the basis for ground and airspace monitoring and control systems now used by airports worldwide. This of course has to do with internal departmental divides, combined with the attention directed by different departments of the VUC towards their respective industrial clusters. Yet, they include the entry of MEMS senor technology into water purifying technologies developed by a small yet growing population of firms in the region—drawing partly on the maritime engineering legacy of the latter. They also include advanced logistics competences (accumulated by the VUC partly through its collaborative linkages towards engineering and electronics) entering into the local production of upmarket foodstuff, allowing this to penetrate markets outside the region.

Conclusion The presence of large, internationally leading universities may boost regional development by means of linear technology transfer and knowledge spillovers to the surrounding environment (see, e.g. Abramovsky & Simpson, 2011). Yet, research-based knowledge travels well, and gravitates towards places where it finds complementary industrial capabilities which do not. Consequently, the direct contribution of university research to regional development is likely to remain limited in all but those few regions which host


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world-leading research in high-velocity fields of immediate relevance to industrial activity. In the Vestfold case, this translates into a situation where industrial firms link up with science system actors elsewhere for the purpose of sourcing advanced, modular science system outputs. Yet, these international technology seekers remain highly dependent on the specialized knowledge asset available primarily in the own organization and the immediate surrounding environment at home. It is in these specialized assets, developed at the intersection between scientific progress and cumulative processes of DUI, we find the potential for cluster mutation and the establishment of new regional development paths. New combinations of knowledge originating in different industries and clusters are rarely identified and explored systematically on a large scale by industry itself. This point to the enduring, even increasing, importance of the local information and knowledge diffusion ecology. In order for this ecology to survive the strains of globalization and serve to explore cross-sector linkages, a stable, committed and inclusive infrastructure is needed which operate independently of inter-firm collaboration at the level of the region. Such can, as the case study above argues, be provided by regional science and education system actors. This broader knowledge externalization, refinement and diffusion role is radically different from that of linear technology transfer based on advanced research; first and foremost because it works through educational programmes rather than technology transfer offices. It does not assume the presence of world-leading research in fields directly relevant to commercial activity, but rather the presence of specialized “industrial” knowledge bases which can be refined and recombined—through research and the education system sensitivity towards their content and value. It is also radically different from traditional cluster thinking, in that it does not see weakening inter-firm innovation collaboration within the region as a threat to the internal consistency of the regional innovation system as a whole. Rather, it sees internationally oriented firms as potential gatekeepers (Giuliani & Bell, 2005; Graf, 2010) which may enrich and diversity the regional knowledge base by means of information and technology transfer into it (Ebersberger & Herstad, 2012; Owen-Smith & Powell, 2004; Simmie, 2003, 2004). Yet, the mobilization and commitment of advanced industrial actors which is necessary to build a foundation for this role requires perceptions of future relevance; and involve choices concerning strategic orientation and content which necessitate that divergent views and preferences on the industry side of the system can be aligned. The process of transformation at the research and education system side will similarly involve establishing legitimacy within a broad range of professional communities; and the institutionalizing of the third-mission role in an organizational context where individual researcher disciplinary excellence and inter-department competition for scarce resources remain key motivation factors (Becher & Parry, 2005; Gibbons, 1994). The development of specialized education programmes thus appear to be critical, because such are the main “carrots” available for industry mobilization. Further, they enable the build-up of new university competences and other “third-mission” activities to be linked directly to the primary roles of universities and university colleges, i.e. that of education in itself. This raises the internal legitimacy of the effort, and lubricates the embedding of the new competences within the organization. As a result, it contributes to decoupling these competences from the industrial organizations in which they originally



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developed. But most importantly, such programmes link directly up to the “main mechanisms for regional knowledge accumulation and diffusion” which remain at play under conditions of the value chain fragmentation and globalization; namely the regional labour market, mobility within it and the resulting formation of personal ties across companies (Agrawal et al., 2006; Sturgeon, 2003) and sectors. Once an education programme “core” has been established, the VUC case illustrate how this may provide the basis for more advanced research activities and increase the overall attention received by the university college from actors spanning the range from local industry to research communities abroad. With this may follow the development and institutionalization of labour markets which in essence overlap between the spheres of industry and university (Lam, 2007). Combined, this increases the potential for attracting researchers and students from abroad, thus further strengthening the role of research and education systems actors as regional loci for information-sharing, personal network formation and knowledge diffusion processes which crosses geographical and sectoral divides. The danger, as our case also shows, is that the system becomes excessively preoccupied with academic excellence in specific disciplines or technological fields, and develop research and commercialization strategies which do not reflect the complexity of industrial activities and come to alienate the industrial side of the equation. This is problematic, because it entails that science and higher education institutions are cut off from a steady supply of experience-based knowledge and insights developed by means of DUI—by industry, on an international scale. From this, it follows that they may drift away from the positions in which they should be placed, at the core of the regional knowledge diffusion infrastructure. Our discussion is based on empirical evidence from a small number of firms in one specialized Norwegian region. This is according to our own line of reasoning an obvious limitation, and we do not claim to have identified a single best practice recipe for regional development in a global economy. What we have done is provide empirical insights into the complexity of knowledge development at the level of the firm, and how this complexity opens some doors for policy intervention and science system support—while closing others, all depending on the contextual conditions at play. From the dynamics described follow numerous questions concerning the long-term impacts of science system actors on regional development, including those related to IPR regulation under conditions where intervention into industrial dynamics assume the active participation of industrial actors—and the main purpose of this intervention is to ensure externalization, diffusion and broader use of specialized knowledge. These questions and limitations translate into a call for future empirical studies which investigate regional knowledge diffusion and cluster mutation policies under different technological circumstances, from a perspective able to combine sensitivity towards the nature of knowledge involved with recognition of the “different” potential roles of regional science and higher education institutions.

Notes 1. NEW knowledge and technology for PACKaging of Microsystems (NEWPACK) was a collaborative research programme founded by the Norwegian Research Council in 2003–2006. 2. MultiMEMS: “Multi-functional MEMS Services” was a collaborative research programme founded by the Norwegian Research Council from 2003 to 2004.

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