INNOVATION MODES, GEOGRAPHY OF KNOWLEDGE FLOWS AND SOCIAL CAPITAL

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1 Paper to be presented at the DRUID-DIME Academy Winter 2009 PhD Conference on ECONOMICS AND MANAGEMENT OF INNOVATION, TECHNOLOGY AND ORGANIZATIONAL CHANGE Hotel Comwell Rebild Bakker, Aalborg, Denmark, January 22-24, 2009 INNOVATION MODES, GEOGRAPHY OF KNOWLEDGE FLOWS AND SOCIAL CAPITAL Ingrid Helene Garmann Johnsen University of Agder Arne Isaksen Department of Working Life and Innovation, University of Agd Abstract: Ingrid Helene Garmann Johnsen, University of Agder, Norway: enrolment 2008, expected final date : The paper attempts to link the theoretical frameworks of social capital and regional innovation systems. The paper examines which specific types of social capital, understood as the institutions, relationships, attitudes and values that govern interaction among people, are most relevant in stimulating the innovation activity in firms dominated by different modes of innovation. The paper distinguishes between the STI (Science, Technology, Innovation) and the DUI (Doing, Using, Interacting) modes of innovation. The empirical part examines aspects of the innovation activity and social capital in four industries in the Agder region in southern Norway. One of these, the process industry, demonstrates clear similarities with the STI mode of innovation, while the three other industries, the ICT industry, the oil and gas equipment supplier industry, and the cultural industry, resemble more the DUI mode. The study demonstrated that the DUI-firms have informal, local relations, few formal, local links, but strong links to external customers. These result support the argument that social capital is often created through participation in civic communities like clubs and associations. The STIfirms, on the other hand, have nearly none informal ties, some formal links to regional knowledge organisations, JEL - codes: R1, -, -

2 Innovation modes, geography of knowledge flows and social capital By Arne Isaksen, University of Agder and Agder Research and Ingrid Garmann Johnsen, University of Agder DRAFT OF PAPER Abstract: The paper attempts to link the theoretical frameworks of social capital and regional innovation systems. The paper examines which specific types of social capital, understood as the institutions, relationships, attitudes and values that govern interaction among people, are most relevant in stimulating the innovation activity in firms dominated by different modes of innovation. The paper distinguishes between the STI (Science, Technology, Innovation) and the DUI (Doing, Using, Interacting) modes of innovation. The empirical part examines aspects of the innovation activity and social capital in four industries in the Agder region in southern Norway. One of these, the process industry, demonstrates clear similarities with the STI mode of innovation, while the three other industries, the ICT industry, the oil and gas equipment supplier industry, and the cultural industry, resemble more the DUI mode. The study demonstrated that the DUI-firms have informal, local relations, few formal, local links, but strong links to external customers. These result support the argument that social capital is often created through participation in civic communities like clubs and associations. The STIfirms, on the other hand, have nearly none informal ties, some formal links to regional knowledge organisations, but generally strong extra-regional relations. The paper demonstrates the potential for more theoretical and empirical studies of how different types of social capital stimulate interactive learning and knowledge flow in regional innovation systems. 1. Introduction The concept of social capital is increasingly seen as one important factor leading to regional economic growth (e. g. Beugelsdijk and van Schaik 2005). The journal Regional Studies devoted, for example, in 2005 one issue (Vol. 39, 8) to social capital. This paper attempts to put the concept of social capital into the theoretical framework of regional innovation systems (RIS). The RIS approach conceptualises innovation as a socially and territorially embedded, interactive learning process taking place through a network of collaborators (Lundvall 1992). Particularly important in regional innovation systems is knowledge flow between the two subsystems of RIS, which are the knowledge infrastructure and the industry, respectively (Cooke et al. 2000, pp ). The knowledge flow between actors in the two subsystems is stimulated by a set of informal rules and joint understanding, i.e. by social capital understood as the institutions, relationships, attitudes and values that govern interaction among people (Iyer et al. 2005; Halpern 2005). Thus, seen in the RIS approach social capital can raise the innovation capability of individual firms and industries in a region by facilitating the flow of knowledge between universities, research institutes etc. and the industry. It is however important to recognise that firms are incorporated in specific types of RIS that may require different types of social capital. A RIS can be defined in both a narrow and a broad way (cf. Lundvall 1992; 2007; Asheim 2009). The narrow definition includes mainly R&D-activities in universities, research institutes and in firms R&D-departments. Innovating firms then often need to be in contact with advanced research institutes and universities. The broad definition of a RIS includes all actors and activities that affect learning, knowledge creation and innovation in a region. A wider set of actors in the knowledge infrastructure will 1

3 then potentially influence the innovation capability of firms, such as actors occupied with vocational and higher education, training, and technological diffusion, and not only those primarily engaged with research as in the narrow definition of the RIS. Different types of social capital will probably be most relevant in stimulating innovation activity in firms making most use of the narrow or the broad version of the regional innovation system. The two versions of RIS include relations to different types of actors, which are relations that may be stimulated by different shared values and rules of social conduct. This paper will analyse in more detail if specific types of social capital are more productive in stimulating innovation activity in some types of RIS than in others. Few other studies exist that explicitly examine the role of social capital in influencing knowledge transfer and innovation activity (Lorenzen 2007). We approach this subject by distinguishing between industries dominated by different modes of innovation. The empirical cases in the paper are four different industries in the region of Agder in the most southern part of Norway. The paper examines the innovation activity and the mode of innovation in the four industries, and where (from which actors and geographical areas) the firms in the industries find information and knowledge for their innovation process. We find that the innovation activity in one of the industries is markedly different from the three others on several aspects. The main research question in the paper is: What are important types of social capital in order to stimulate innovation activity in the four industries in Agder? 1 The remainder of the paper consists of three main parts. Next follows a discussion of the theoretical framework of the paper focusing on modes of innovation, regional innovation systems, and social capital and networks. Part three includes a description of the data material, and the empirical analyses of innovation activity, knowledge sources and social capital in the four different industries in Agder. Finally, the concluding part sums up the empirical results and discusses further theoretical lessons from the study of the four industries. 2. Modes of innovation and social capital A recurrent question in the paper is how different types of social capital influence knowledge flow and innovation activity in specific types of industries. We distinguish in particular between industries with different innovation modes. The theoretical discussion starts by introducing two contrasting types of innovation modes, and ends trying to characterise the type of social capital that, in particular, may stimulate innovation activity in the two modes. Modes of innovation A basic distinction among the innovative activity of firms is the two modes of innovation denoted as the STI (Science, Technology, Innovation) and the DUI (Doing Using, Interaction) modes (Jensen et al. 2007). The two innovation modes are combined in individual firms and in specific industries. They are, however, analytical concepts used in this paper to characterise main aspects of knowledge creation and innovation processes in firms and industries. The STI mode describes important elements of the innovation activity in firms dominated by, in particular, analytical (scientifically based) knowledge (Coenen and Asheim 2006; Lorenz and Lundvall 2006). Much of the innovation activity takes place in in-house R&D 1 We are aware that social capital can have negative effects (see for instance Halpern 2005 or Putnam 2000). The possible negative effects of social capital, however, will not be discussed in this paper. 2

4 departments, in research intensive small firms, and in universities and research institutes, and with the intention of developing fairly radical innovations (Lundvall and Johnson 1994, p. 27). The knowledge creation is in large part based on development and testing of formal, scientific models. These activities require analytical knowledge, but may also involve synthetic (engineering based) knowledge in, for example, the design and redesign of prototypes, and symbolic (art based) knowledge in marketing of new products or services (e.g. Moodysson 2007). STI-innovating firms are above all found in high technology industries, such as biotechnology and microelectronics, which are the industries with the highest relative R&D-costs (OECD 2007). The division between the STI and the DUI innovation mode underlines, however, that not only high-technology and knowledge intensive firms perform innovation activity, but that this is a more general activity in industries. The important point is that firms innovate in different ways and, thus, that the reliance on mainly analytical knowledge as in the STI mode is one alternative. Much analytical knowledge is easily codified, i.e. encapsulated in and exchanged through language or symbols. Although codified knowledge is not manna from the heavens, it may be easily available around the world (Iyer et al. 2005, p. 1019). Thus, the flow of analytical knowledge is to a large extent global and involves researchers in firms, universities etc. which may be widely dispersed geographically (Moodysson 2008). These researchers are often members of the same epistemic communities consisting of persons with similar knowledge bases and which exchange mainly analytical knowledge (Amin and Cohendet 2004, pp ). The STI innovation mode is linked to the narrow definition of a regional innovation system, which focuses on interactive learning between, in particular, firms R&D-departments and universities and research institutes. Although the contact may involve partners in different parts of the world, as underlined above, some firms benefit from close geographical distance to research institutions, both to gain early access to new research results and to recruit highly educated labour. Such advantages partly explain why firms in new, knowledge intensive industries, such as biotechnology, often cluster close to some universities and research institutes (Cooke 2002, page ). Successful biotechnology clusters typically constitute local nodes of excellence in global networks (Gertler and Levitte 2005). The DUI model describes innovation processes in firms dominated by first of all synthetic (engineering based) knowledge, but also symbolic knowledge. Innovations occur mainly as incremental changes in products and processes based on experiences and competence acquired on the job as employees face new problems, and in cooperation with in particular customers and suppliers (Jensen et al. 2007). The new solutions are often based on novel combinations of existing knowledge. Although there is no uniform correspondence between synthetic and tacit knowledge, synthetic knowledge includes important tacit elements as the knowledge often cannot be formally codified. This makes the exchange of synthetic knowledge more complex. Asheim and Gertler (2005) maintain that tacit knowledge does not travel well, and the exchange of tacit knowledge may require shared experience and face-toface interactions. Physical proximity is then an important premise for the sharing and transmission of synthetic knowledge. The flow of synthetic knowledge occurs mainly on two geographical levels. One level is between customers, producers and suppliers in national and international value chains, and in particular when producers are engaged in solving new problems for customers. The other level is inside firms and in local communities of practice that includes groups of persons 3

5 performing similar tasks (Amin and Cohendet 2004, pp ). The knowledge that is created and shared in communities of practice is often context specific and difficult to codify, which implies that geographical proximity facilitates cooperation in such communities. The DUI innovation mode is linked to the broad definition of RIS that includes all actors and activities that affect learning, knowledge creation and innovation in a region. In this meaning of RIS, universities fulfil other functions than being immediate sources of innovation, such as educating skilled workers (Lundvall 2007, p. 97). The incremental innovations dominating in the DUI mode often require efforts from experienced and skilled workers, possibly accompanied by inputs from external experts. DUI-innovating firms thus rely on a specialised labour marked and a local technical culture, where knowledge is created, maintained and shared in cooperation between firms, education institutions, specialised consulting firms etc. The DUI innovation mode also requires that the work environment is designed to promote learning through problem solving and effectively use the skills of many types of employees for innovation (Lorenz and Valeyre 2006). The organisational form can then be characterised as either learning or lean forms of work organisations. Both forms demonstrate strong learning dynamics and (rely) on employees contribution to problem-solving (Lorenz and Valeyre 2006: 145). It demands cooperation and knowledge flow inside organisations. The STI innovation mode benefits also from these kinds of work organisations, but basically requires a high internal absorptive capacity to make firms able to find and employ external, scientific knowledge (Cohen and Levinthal 1990). Social capital and networks Both types of innovation modes imply that the exchange of knowledge between different actors is an important premise for innovation activity. In line with the RIS approach, these actors are first of all firms and different types of knowledge organisations. However, the exchange of knowledge takes place between specific persons within these firms and knowledge organizations, for example between engineers and researchers in firms and R&D institutes. Individuals can often be seen to represent the organisations (for instance firms) that they belong to (Lorenzen 2007). These persons, which collaborate in innovation processes, might belong to specific communities of practice or epistemic communities, where different sets of institutions or rules of the game guide the exchange of knowledge and information. These institutions, that lay the premises for the exchange of knowledge and information, will probably vary between different communities and industries. We will employ social capital theory to explore in more detail the importance of different types of social relations and institutions for the exchange of knowledge and information between actors belonging to specific communities. Bourdieu (1986) was one of the first scholars in modern social theory to introduce the concept of social capital. At the core of his analysis is the preoccupation with social inequality. Bourdieu s main argument is that social capital helps reproduce social inequality because people that belong to the social elite primarily use this form of capital to maintain their position in society. Coleman (1988; 1994), on the other hand, argues that social capital not only benefits the social elite, but that it can also benefit those of lower social status. He makes a distinction between human capital and social capital. Human capital is seen as an individual asset, while social capital is a collective good. Social capital is thus created in the links between individuals or actors, and it is a resource that is available to the individual or actor through their social relationships. 4

6 The concepts of social capital as defined by Bourdieu and Coleman are important when it comes to the study of RIS. While Bourdieu sees social capital as an individual asset, Coleman sees it as a collective asset that is independent of social groups or status, and that it is a useful resource that can be created between actors (Westlund 2006). What Bourdieu and Coleman both have in common, however, is the view that social capital is inherent in the social structure (op. cit.). Important here is the individual versus the collective aspect of social capital. Social capital is created in the links between actors that can be individuals, organisations or firms. Innovation system theory tends to focus on interaction between institutions and organizations, and the individual aspect thus tends to be ignored. In order to incorporate the individual into the study of innovation systems, one can follow Cooke s (1998) argument that innovation system can be seen as a social system where innovations are a result of social interaction between actors, that is, individuals or organizations. The term interaction is thus important in explaining innovation, and interaction is stimulated by shared norms, values, and understanding. Therefore, social capital often affects these organisations, and can be seen as an important analytical tool in order to understand the knowledge flow within and across organisations. The importance of interaction brings us to the next key concept in social capital theory; that of social networks. A social network can be defined as a social structure made of actors (most often seen as individuals or organizations) that are tied by one or more types of interdependency, that is, ideas, friendship, kinship, conflict, etc. Granovetter (1973) makes a distinction between strong and weak ties in the network. Strong ties refer to individuals that are tied to one another by kinship, close friendship etc. and who are frequently interacting with each other. Weak ties, on the other hand, consist of individuals that are loosely tied to each other and who interact occasionally or rarely. While Granovetter s concept of the strength of ties captures differences in social ties in the civic realm, the concepts of tightly coupled and loosely coupled ties are meant to capture differences in social ties in the business realm (Lorenzen 2007). Tightly coupled ties are long-term networks of stable value chains or strategic alliances that bind together homogenous actors, while loosely coupled ties are short termed alliances like for instance projects that bind together actors from different social groups (Lorenzen 2007). A distinction can be made between bonding (exclusive) and bridging (inclusive) social capital (Putnam 2000). Bonding social capital refers to social networks that are inward looking and tend to reinforce exclusive identities and homogeneous groups (Putnam 2000, p. 22). Examples of bonding social capital can be ethnic fraternal organizations, church-based women s reading groups etc. But bonding social capital can also lead to negative behavior and exclusivity, example of this can be criminal gangs (see for instance Halpern 2005). Bridging social capital refers to outward-looking networks that encompass people across diverse social cleavages (Putnam 2000, p. 22). Examples of these can be civic rights movements, youth service groups etc. The examples of bonding and bridging social capital show that social networks of individual or groups can enhance community productivity and cohesion, whereas self-serving exclusive groups such as criminal gangs, which operate against societal interests can be seen as negative for society. As for the business realm, Halpern (2005) argues that the firm can be viewed as bonding social capital. This means that individuals in the firm form a relatively dense network governed by shared norms and objectives. He further argues that between-firm social capital can be characterised as bridging, indicating how firms network with other firms in order to get hold of valuable information that is important for their innovation process. If a firm is too tightly bonded, it may neglect its bridging social capital, that is, connections to markets, suppliers and competitors (Halpern 5

7 2005). Successful firms thus show a balance of investment between bonding social capital (within-firm) and bridging social capital (between-firm), and avoid overinvestment in any of the two forms (Halpern 2005). Social networks can also be formal or informal (Allen et al. 2007). Formal networks are systematically established in order to transmit information through defined relationships. This type of network follows organizational structures defined by organizational charts, etc. Informal networks, on the other hand, have no permanent structure, and often emerge from shared experiences or interests between individuals in organisations. Informal social networks can serve to co-ordinate social interaction through social monitoring, gossip and reputation effects, like in business clusters characterised by local buzz (Bathelt et al., 2004; Lorenzen 2007). Lorenzen (2007) argues that even though tightly coupled business relations rarely demand face-to-face meetings, many business networks are still clustered. This means that they are often initiated through civic relations, that is, among managers in local communities. These relations are often established through participation in clubs, associations etc. In addition to the characteristics of social relations, social capital theory emphasizes the importance of institutions, that is, informal rules that govern the behaviour of the actors within the social structure. Shared norms and values as well as a shared language facilitate the exchange of information between individuals. Social relations that draw upon particular institutions to achieve co-operation and communication lead to social traits such as trust, participation, etc. (Lorenzen 2007). Further, Lorenzen (2007) argues that learning processes are highly local because they are facilitated by a local system of regulative, normative and cognitive institutions. Since institutional learning processes create communities, learning is often most efficient in dense social relations. Social institutions, then, are geographically limited because they are created in social relations (Lorenzen 2007). Institutional proximity, that is, a set of common norms, habits and rules of the game for behaviour in business relations, is particularly important for the exchange of tacit knowledge (Boschma 2005). Institutional proximity reduces uncertainty and transaction costs in innovation collaboration. Transmission of codified knowledge is more easily transferred despite institutional distance. To summarise, we argue that social capital is created in the link between actors (individuals, firms, organisations); it is thus a collective rather than an individual good. Social capital is governed by social institutions and is based on shared conventions, i.e. trust, participation, inclusion, and norms ( rules of the game ), as well as sanctions (i.e. punishments and rewards) that help maintain the norms and networks. Trust between the actors in the network can be seen as an important premise for the maintenance of social capital. In addition, geographical proximity can facilitate the creation of social capital because of the shared conventions and norms that govern the behaviour of actors within a geographical area. As STI-innovating firms are mainly dependent on analytical knowledge that is easily codified, these firms are not dependent on tightly coupled relations to local knowledge organizations. Rather, it is likely that these firms have high bridging social capital at the national and global levels, and thus tighter relations within epistemic communities nationally and globally that have specialised knowledge that the firms need in their innovation process (Table 1). DUIinnovating firms, on the other hand, are likely to have high bridging social capital at the local level and thus tighter relations to many local actors, to some important customers, and looser relations to extra-regional actors in general. Tightly coupled local relations benefit from shared institutions, language etc. that facilitate cooperation and enables trust between actors. Tightly coupled global relations are in particular dependent on continuous investments, 6

8 because they do not benefit from the trust already obtained between local firms. In addition, these relationships require establishment of a common set of institutions in order for the transmission of information to be successful. With this we argue, contrary to some scholars (see for instance Lorenzen 2007), that social capital can be found at the local, national and global levels. Table 1: Analytical framework Innovation mode STI DUI Important knowledge flow With knowledge organisations Along the value chain Geography of innovation Globally (in epistemic communities) Locally (in communities of practice) and globally (in value chains) Type of social capital High bridging social capital nationally/ globally High bridging social capital locally Characteristics of the social networks Tightly coupled relations to knowledge organizations nationally/ globally, loosely coupled, local relations Tightly coupled relations to communities of practice, to some demanding customers, and loosely coupled relations outside the region 3. Innovation mode and social capital in Agder The theoretical part above claims that the social capital concept can be used as an analytic tool in order to understand how different forms of interactions between actors can facilitate knowledge creation in different types of firms and industries. We argue that social capital triggers knowledge transfer, but that the transfer of different forms of knowledge (i.e. analytical vs. synthetic) is stimulated by different types of social capital and networks (bonding vs. bridging social capital, tightly coupled vs. loosely coupled relations, informal vs. formal networks). These ideas constitute the basis for the empirical analyses of innovation activity in four different industries in the Agder region of Norway. The theory based research questions for the empirical study are 1) what type of innovation mode that dominates in the four industries, 2) which knowledge sources (type of actors and locations) that are most important in each industry, and 3) what type of social capital that dominate in each industry. Data description The empirical study of innovation processes and forms of learning in these four industries in Agder builds on a web-based survey. The survey was carried out during the end of 2007 and the start of The questionnaire is quite extensive, and it includes questions regarding basic information about the firms; firms core competence and learning; firms innovation activity, R&D and patenting; idea and knowledge sources for innovation; regional factors stimulating and hampering innovation; and regional cooperation and networks. The questionnaire was sent to 197 firms. These include all 41 firms participating in the regional network NODE (Norwegian Offshore and Drilling) at the time of the survey, all 12 process firms that are members of the Eyde network, and all 72 firms seen to be part of the regional ICT industry to the information of a regional organisation (Conventure) working to support firms and networking in this industry. This selection procedure ensured that nearly all oil and gas equipment suppliers, process firms and hardware and software ICT firms in Agder were registered. The cultural industry is more heterogeneous. It also consists of many 7

9 individual enterprises and is difficult to overview. We decided to concentrate on a few, supposedly innovative sectors of the cultural industry, i.e. architecture, design, film, and design intensive manufacturing. Based on the telephone catalogue, web sites and inquiries to municipalities a list of 62 firms in these industries were made. The managers in small firms and the technical directors etc. in larger firms were asked to answer the questionnaire. The response rate is about 50 percent after several rounds of reminding (Table 2). The last reminder consisted of telephone calls to contact persons in the largest firms, and the sample includes almost every firm with more than 10 employees. It is difficult to find statistical figures for the number of jobs in the four sectors as these do not always correspond to the two digit NACE sectors that are available on the county level from Statistics Norway. However, calculations indicate clearly that the sample of ICT firms, equipment suppliers and process firms in the survey includes a substantial share of the jobs in these sectors in Agder, and the sample should then give a good picture of these industries in Agder 2. The culture industry in the survey includes a few small industrial sectors where the number of jobs is not available in the official statistics. Table 2: Size of the survey sample Industrial sector Number of firms Response rate Number of jobs ICT firms Suppliers of equipment for the oil and gas industry ,488 Process firms (smelteries etc.) ,936 Culture firms (architects, designers, film companies, design intensive manufacturing firms) SUM ,456 Characteristics of the firms The four industrial sectors have some specific characteristics. The process firms (smelteries etc.) are clearly the oldest and largest ones, and all these firms are part of larger corporations (Table 3). These are production units that largely employ skilled workers. The firms produce mainly standardised products in large quantities, but they also to some extent adapt products to individual customers. The equipment suppliers are also quite old and large, although they include a mix of old and new, small and larger firms. These are more often engineering firms that produce small batches or one-off products (such as drilling, loading and anchoring equipments, and cranes) adapted to individual customers. Nearly half of the equipment suppliers are part of larger corporations. The two other sectors include much smaller firms, although three of the ICT firms in the sample have about 100 employees. The ICT firms are often software producers with many higher educated employees. The culture firms in the sample (such as architects, designers and 2 The chemical manufacturing industry and metal production (NACE 24 and 27) have about 2500 jobs in Agder, while the process industry firms in the sample have more than 1900 jobs. Manufacturing of machinery and equipment (NACE 27) includes about 2800 jobs in Agder, and the equipment suppliers in the sample have nearly 2500 jobs. As regards the ICT industry, the sectors Office machinery and equipment, Electrical machinery and apparatus, Radio, television and communication equipment and apparatus, and Computer and related activities (NACE 30, 31, 32 and 72) includes 1900 jobs at Agder, and the sample of ICT firms in the survey includes 750 jobs. 8

10 film producers) also have many higher educated staff. These are mainly small firms, locally owned, and also characterised by a high degree of customised products and services. Table 3: Basic information about the surveyed firms Industrial sector Average age in years (in 2008) Average number of jobs in 2007 Share of firms where more than 50% of the employees have higher education Share of firms that are part of a larger corporation ICT firms Equipment suppliers Process firms Culture firms The sample reflects the situation of strong economic expansion over several years when the survey was carried out. Thus, most of the firms report increasing turnover the last five years. This is in particular the case for the equipment suppliers which have experienced an enormous increase in the market for equipments to the oil and gas industry following the rise of the oil prices (Table 4). Also a large share of firms in the three other sectors has experienced growth. Table 4: Firms assessment of changes in the last five years (until 2007) or since the start-up Industrial sector Share of firms with increasing turnover Share of firms with an increasing number of employees ICT firms Equipment suppliers Process firms Culture firms Innovation activity The surveyed firms are in general innovative. This includes in particular the ICT firms and the equipment suppliers. Thus, all ICT firms and 90 percent of the equipment suppliers report having introduced new or significantly changed products or services on the market the last three years. The corresponding figures for the culture firms and the process firms are 60 and 37.5 percent. About percent of the turnover in the sectors comes from new or significantly improved products or services the last three years (Figure 1). This is a standard indicator in innovation studies, such as in the Community Innovation Survey. Figure 1 demonstrates much higher figures in Agder than found in, for example, the manufacturing industry in Norway, in which 11 percent of the turnover in 2006 comes from new or significantly improved products the last three years 3. However, the high innovation activity reported in the VRI survey may reflect the type of industry studied. Thus, some industrial sectors in Norway, in particular manufacture of communication equipment (NACE 32), have a high share of turnover from new or significantly improved products, as much as 51 percent for NACE 32. Other innovation indicators in the survey also point to the fact that the survey consists of a group of fairly innovative firms. A majority of the firms have started to use new or 3 Source: Innovasjonsundersøkelsen 2006 (The Innovation Study 2006), Table 11.3a. Statistics Norway 9

11 significantly changes processes, components or materials the last three years, and have been innovative as regards new or changed strategies and organisational structures. Figure 1: Share of turnover in new or significantly changed products/services the last three years Share of turnover ICT firms Equipment suppliers Process firms Culture firms What is then the dominating innovation mode in the firms? In analysing this question, Jensen et al. (2007) develop a number of indicators to distinguish between the STI and DUI modes of innovation. The STI-indicators focus on expenditures on R&D, higher educated employees and cooperation between firms, universities and research institutes. Table 5 builds on these indicators. The process firms most clearly resemble the STI mode of innovation, as most of these firms have a R&D-department, finance R&D in the firms and buy R&D from external actors. The culture industry, on the other hand, has very few firms with the characteristics linked to STI-firms. Also a smaller share of the ICT firms and the equipment suppliers has a R&D department and buy R&D from external actors. Looking more carefully at the firms with R&D-departments, we see that these generally are larger than those without R&Ddepartments. The average size is 81 and 12 employees, respectively. Table 5: Firms with R&D-activity Industrial sector Share of firms with an R&D department or unit Share of firms that have financed internal R&D the last three years Share of firms that have bought R&D from external actors the last three years ICT firms Equipment suppliers Process firms Culture firms The indicators used to capture the DUI mode of innovation in Jensen et al. (2007) focus on organisational learning and on close relations to customers. Adapting some of these indicators to the VRI survey, we find that the process firms make less use of project organisation and autonomous work teams than the other three industries. Customers are important sources of ideas for innovation in all industries, however, least important in the process firms. To conclude, we find some differences in dominating innovation mode between the four industries in Agder. The process firms have the most, and the culture firms the least, similarities with the STI mode. The ICT firms and equipment suppliers have elements of both the two modes, however, are most similar with the DUI mode of innovation. 10

12 Table 6: Firms with R&D-activity Industrial sector Share of firms that to a large extent organise work in projects Share of firms that to a large extent delegate responsibility to autonomous work teams Share of firms seeing inquiry from customers as very important sources of ideas for innovation projects ICT firms Equipment suppliers Process firms Culture firms Location of important sources of knowledge Questions about the location of important knowledge sources are used in the VRI survey in order to capture from where the firms gather knowledge for their innovation process. This can also say something about the importance of the regional environment for the firms ability to innovate. Looking first at the knowledge sources, most firms report that knowledge sources inside the firms are very important, and for process firms also other firms within the industrial enterprise (Table 7). Next follows customers, except for cultural firms. This is crudely speaking the result found in most quantitative innovation surveys. All other knowledge sources than the firm/enterprise and customers are of less importance in the VRI survey. Table 7: Very important sources of knowledge for firms innovation activity the last three years Equipment Process Cultural ICT firms suppliers firms firms Inside the firm Other firms in the enterprise Customers Component suppliers Suppliers of machinery etc Competitors Other specialised firms Consultants Universities Research institutes Conferences, journals Trades, exhibitions According to the findings, a large part of what the firms consider to be important knowledge sources are located outside Agder. The main picture for some important sources of knowledge and the four industries together is shown in Figure 2. Universities and R&D-institutes are the most important knowledge sources locally. Going into more detail, we find that ICT firms, equipment suppliers, and process firms find knowledge organizations like universities to be the most important sources of knowledge in Agder, while the culture firms generally refer to actors in the value chain as the most important regional knowledge sources. A large part of the important knowledge sources are found at the national level. In the ICT firms, equipment suppliers, and culture firms, actors like customers, competitors, suppliers, and specialised firms tend to dominate as knowledge sources at the national level. The 11

13 process firms refer to knowledge organizations, and to some extent suppliers, as most important at the national level. At the global level, the process firms (which all are externally owned) in general have more connections to important knowledge sources than the other firms. Here, research organisations as well as customers stand out as important actors. The culture firms and equipment suppliers in general have very weak connections outside of Norway. Figure 2: Location of important knowledge sources for firms innovation activity. All firms Local region Rest of Agder Rest of Norway Rest of world Conferences etc. R&D-inst. Universities Component suppliers Customers 0 % 20 % 40 % 60 % 80 % 100 % Share of firms finding important knowledge sources in different locations Overall, the ICT firms tend to consider experience-based knowledge from customers and suppliers to be more important than analytical or formal knowledge that stem from research based activities. Important knowledge sources are mostly found at the national level. The equipment suppliers do not seem to consider regional actors to be of great importance either, but they have fairly strong connections with customers, competitors, suppliers, and specialised firms at the national level. The culture firms consider knowledge from research organisations to be least important among the firms. In general, they rely on knowledge from actors in the value chains both locally and nationally. The process firms also consider actors at the regional level to be of less importance for gaining important knowledge, while actors at the national and international levels are more important. This means that both research organisations and actors in the value chain that are situated outside the region serve as important knowledge sources. Social capital and networks - Importance of tightly and loosely coupled relations Important in regional innovation systems is the knowledge flow between the two subsystems of RIS, i.e. the firms and the knowledge infrastructure. Measurements of the frequency of collaboration between these subsystems can say something about the strength of the relations between them. In the VRI survey, the firms were asked how often they collaborate with different actors in Agder. The findings demonstrate that the ICT firms, equipment suppliers, and culture firms have fairly weak relations to research institutes at Agder, since a large majority of these firms report to collaborate rarely or never with these actors (Table 8). The process firms seem to have stronger relations to the research institutes at Agder, since the majority of the firms report to collaborate occasionally with these actors. 12

14 Table 8: Frequency of collaboration with research institutes at Agder Collaborate frequently Collaborate occasionally Collaborate rarely or never ICT firms Equipment suppliers Culture firms Process firms When it comes to customers in Agder (Table 9), the process firms have fairly weak connections to these actors, while firms in the three other industries collaborate more frequently with customers at Agder, and are thus expected to have stronger connections to these actors. The same findings apply for frequency of collaboration with other firms at Agder within the same segment (Table 10). The ICT firms, equipment suppliers, and culture firms collaborate more frequently with these actors than do the process firms. Table 9: Frequency of collaboration with customers at Agder Collaborate frequently Collaborate occasionally Collaborate rarely or never ICT firms Equipment suppliers Culture firms Process firms Table 10: Frequency of collaboration with other firms at Agder within the same segment Collaborate frequently Collaborate occasionally Collaborate rarely or never ICT firms Equipment suppliers Culture firms Process firms These findings reinforce the tendency that firms that resemble the DUI mode of innovation (i.e. ICT firms, equipment suppliers and cultural firms) are more likely to find innovating partners that are dominated by experience based knowledge bases locally. The process firms, which are dominated by the STI mode of innovation, have stronger connections to extraregional actors that are dominated by analytical knowledge bases. These firms are also more closely tied to knowledge organisations locally, but in general have fairly weak connections to actors in the region. When it comes to the knowledge flow in the RIS, the general tendency points towards a fairly weak innovation system, where national or international sources of knowledge is more important for the firms ability to innovate than sources at the local or regional levels. 13

15 Importance of formal and informal social networks Social networks that stimulate knowledge transfer within the cluster can be formed on both a formal and an informal basis. The importance of formal and informal social networks can say something about which actors and what types of arenas the firms use in order to gain important knowledge for their innovation process. Table 11 shows the importance of participation by managers and employees in local informal arenas in their leisure time for the development of firm s ability to innovate. Involvement by managers and employees in local work-related formal networks constituted of other firms is considered to be important for the majority of the firms (Table 11). These types of networks are established by the firms themselves, and consist of other firms within the same segment. The formal networks are, contrary to informal arenas, seen as important also by the process firms. Table 11: Importance of participation by managers and employees in work-related formal networks that are in large part constituted of firms Very important Important Less important ICT firms Oil and gas firms Culture firms Process firms The ICT firms, culture firms, and, in particular, the equipment suppliers consider informal social networks to be important. This means that civic social arenas are useful for establishing relationships and gaining important information. The majority of the process firms consider informal social networks to be of less importance. One explanation for this can be that much of the knowledge used in the innovation process by these firms is formal analytical knowledge that is easily codified, and often found in national and international knowledge organisations. Informal, local arenas are then less important for obtaining this type of knowledge. Table 12: Importance of participation by managers and employees in informal arenas in the local environment for the development firm s ability to innovate Very important Important Less important ICT firms Equipment suppliers Culture firms Process firms Conclusion This paper attempts to put the concept of social capital into the theoretical framework of regional innovation systems. The paper in particular examines if specific types of social capital are most relevant in stimulating the innovation activity in firms dominated by different modes of innovation. The paper thus distinguishes between the STI and the DUI modes of innovation, which are mainly based on scientific, analytical knowledge and experience based, synthetic knowledge, respectively. The theoretical framework of the paper proposes that firms dominated by the STI mode have high bridging social capital at the national and global levels and tightly coupled relations to, in particular, national and international, knowledge organizations, and often more loosely coupled relations to the regional innovation system. 14

16 DUI-innovating firms are, on the other hand, supposed to have high bridging social capital at the local level and tightly coupled relations to local communities of practice, to some demanding customers, but otherwise rather loosely coupled relations outside the region. The empirical part of the paper examines aspects of the innovation activity and social capital in four industries in Agder. One of these, the process industry, demonstrates clear similarities with the STI mode of innovation, while the three other industries, and in particular the cultural industry, resemble more the DUI mode. The main research question is what regional factors and types of social capital that are important to stimulate innovation activity in the four industries in Agder. The empirical analysis demonstrate that the ICT firms, equipment suppliers and culture firms, characterized mainly by the DUI mode of innovation, have fairly weak connections to other regional actors, especially to knowledge organisations. The extra-regional relations seem to be stronger and are considered as more important for the firms ability to innovate. At first sight, these findings do not correspond with the assumption that DUI-firms have stronger local relations and weaker relations that reach outside the region. However, it must be mentioned that these firms first of all have strong links to external customers, and that the firms see local, informal networks as important for their ability to innovate. The last result supports the argument by Lorenzen (2007) that social capital is often created through participation in civic communities like clubs, associations etc. Even if informal, local networks are important, our findings indicate that the regional innovation system in Agder is fairly weak, as it is characterised by rather little knowledge flow between regional knowledge organisations and the important DUI-industries. The process firms, characterized mainly by the STI mode of innovation, have the strongest connections to local knowledge organisations. These firms, however, consider informal local networks to be of less importance. This can reflect the fact that all the process firms are part of externally owned corporations. The process firms have in general quite strong connections that reach outside the region, which correspond with the assumption that firms that innovate according to the STI mode have weaker local relations and stronger extra-regional relations. Except for the importance of informal, local relation among the DUI-innovating firms, the VRI survey concludes that national relations and actors are more important than regional ones in stimulating innovation. This corresponds with other empirical studies of various regional industries in Norway (Onsager et al. 2007, Isaksen 2008). Based on the VRI survey, we find that social capital in the firms that have the most similarities with the DUI mode is characterised by bridging social capital at the local and national levels. These firms rely on local, informal social networks in order to get hold of important knowledge. The tightly coupled relations (or strong ties) in these firms are in most part connected to communities of practice locally and to customers nationally, while the connections at the international level are more loosely coupled. The social capital of the firms dominated by the STI firms is characterized by bridging social capital at the local, national and international levels. But these relations are in most part restricted to knowledge organisations. The STI firms thus have tightly coupled relations at the national and international levels that are mostly related to knowledge organisations, and have loosely coupled relations to actors at the local level, except to knowledge institutions. Are there some more general theoretical lessons originating from this study? We think that the concept of social capital has proven to be a useful tool in order to understand more about the 15

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