همکاری شرکت ها و حالت های نوآوری در نروژ

This paper examines the sources of firm product and process innovation in Norway. It uses a purpose-built survey of 1604 firms in the five largest Norwegian city-regions to test, by means of a logit regression analysis, Jensen et al.’s (2007) contention that firm innovation is both the result of ‘Science, Technology and Innovation’ (STI) and ‘Doing, Using and Interacting’ (DUI) modes of firm learning. The paper classifies different types of firm interaction into STI-mode interaction (with consultants, universities, and research centres) and DUI-mode interaction, distinguishing between DUI interaction within the supply-chain (i.e. with suppliers and customers) or not (with competitors). It further controls for the geographical locations of partners. The analysis demonstrates that engagement with external agents is closely related to firm innovation and that both STI and DUI-modes of interaction matter. However, it also shows that DUI modes of interaction outside the supply-chain tend to be irrelevant for innovation, with frequent exchanges with competitors being associated with lower levels of innovation. Collaboration with extra-regional agents is much more conducive to innovation than collaboration with local partners, especially within the DUI mode.

There has traditionally been a strong dividing line in the research looking at the sources of innovation. This dividing line has been fundamentally determined by the value different strands of research award to science and technology as the key element for the generation, diffusion, and assimilation of innovation. Researchers on innovation have, over the years, tended to place themselves on either side of the dividing line. On one side of the line, the linear model of innovation (Bush, 1945 and Maclaurin, 1953), and research on knowledge spillovers (Audretsch and Feldman, 1996, Cantwell and Iammarino, 1998 and Sonn and Storper, 2008) have looked at innovation from a scientific and technical perspective. This has led to the use of research and development (R&D), patenting, information and communications technology (ICT) expenditures, and the level of education and training of the labour force as the main proxies of, as well as the key factors behind, the development and assimilation of innovation. Other researchers have, by contrast, been profoundly sceptical about the relevance of R&D, patenting and ICT expenditure as sources of innovation relevant to the firm (Cooke, 2001). These researchers on the other side of the dividing line have tended to place the greatest emphasis on institutions, interactions, networks and informal relationships that facilitate the generation and exchange of knowledge (Lundvall, 1992). This strand has given rise to a blooming literature which, under different definitions and names – e.g. ‘neo-Marshallian industrial districts’ (Becattini, 1987), ‘innovative milieux’ (Aydalot, 1986), ‘learning regions’ (Morgan, 1997), or ‘regional innovation systems’ (Cooke et al., 1997 and Cooke and Morgan, 1998) – regards innovation as a territorially embedded phenomenon, determined by the social and institutional conditions in a given territory (Iammarino, 2005). A number of scholars have tried to bridge the gap between linear approaches to innovation and those more concerned with institutions and interactions, often putting the capacity to assimilate external knowledge at the heart of the process of innovation. von Hippel (1976), for example, focused on how user–supplier relationships shaped innovation in the production of scientific instruments. Cohen and Levinthal (1990) introduced the concept of absorptive capacity in the firm, making it not only dependent on the firm's prior related knowledge and R&D expenditure, but also on a firm's interdependence with rivals and history – and path-dependent. Chesbrough (2003) has put forward the idea of open innovation, which has propelled to the fore the view that innovation – in contrast to prior paradigms which emphasised the benefits of in-house innovation, closed to external influences – is increasingly the result of a combination of ideas from both internal and external sources. Other attempts have adopted a more macro-approach, using regions and metropolitan areas as their unit of analysis (e.g. Crescenzi et al., 2007 and Rodríguez-Pose and Crescenzi, 2008). One of the most prominent recent attempts to connect internal R&D-based and external, institutional- and interaction-based innovation has been that of Jensen et al. (2007). These authors identify two fundamental modes of firm learning: ‘Science, Technology and Innovation’ (STI) and ‘Doing, Using and Interacting’ (DUI). The STI-mode of innovation refers to the use of scientific knowledge in the development of new technologies that form the basis of new products or processes within the firm. The DUI-mode refers to on-the-job problem-solving based on the exchange of experiences and know-how, through which firms find solutions to various problems that arise. These processes typically involve a large component of tacit knowledge (Jensen et al., 2007, pp. 62–64). According to Jensen et al. (2007), the STI and DUI-modes of innovation have used different approaches, techniques, and proxies to explain and measure how innovation at the level of the firm is generated. The STI-mode has generally relied on deductive approaches and quantitative techniques, employing R&D, patenting, ICT and the formal education of the workforce as the key indicators. The DUI-mode of innovation is somewhat more diverse, although inductive and qualitative approaches have tended to prevail. Despite the increasing importance of quantitative analyses focusing on Community Innovation Surveys (CIS), these authors consider that quantitative methods based on survey data have still played a relatively small role in DUI-mode approaches: “The vast majority of quantitative survey-based studies of innovation simply had little to say about the relation of DUI-mode learning to innovative performance” (Jensen et al., 2007, p. 681). This is partly a result of the difficulty in operationalising the complex institutional and relational factors at the base of DUI-mode approaches to innovation, but also a consequence of a general belief that processes such as learning by doing and using are best analysed through in-depth case studies. Jensen et al. apply latent class analysis to data from 1643 Danish firms and uncover that the two modes of innovation are complementary. Firms which combine STI and DUI-innovation are more likely to introduce new products and services than those specialised in either of the modes (Jensen et al., 2007). While making a pioneering and important contribution to our knowledge, one of the potential downsides of Jensen et al.’s analysis is that the classification of firms into four clusters according to the intensity of use of STI and DUI-modes of innovation by each firm creates a rather crude division which represents the variables of interest in the logistic regression analysis on which the key conclusions are based. This implies a significant loss of information about STI and DUI-modes of learning at the level of each firm. In this paper we aim to make a contribution to this debate by analysing to what extent STI and DUI-modes of innovation are related to firm level innovation in Norway. We use a specifically tailor-made survey of 1604 firms with more than ten employees in the five major Norwegian city-regions. The survey measures the different types of interactions that these firms engage in. We classify the interactions with different partner types into STI-interaction types and DUI-interaction types. STI-interaction types include connections with universities, research institutes, and consultancy firms. DUI-interaction types encompass linkages with other firms in the conglomerate, suppliers, customers, and competitors. DUI-type interactions are, in turn, divided into those that fall within the regular supply-chain (interactions with suppliers and customers), and those which do not (interactions with competitors). The main contributions of this paper lie in four areas. First of all, in the use of different measures of innovation. In contrast to previous work, which tends to differentiate between product and service innovation (Jensen et al., 2007 and Kirner et al., 2009), we distinguish, on the one hand, between product and process innovation, defined as the introduction of new products or processes in the firm over the last three years, and, on the other, between incremental and radical innovation. This gives us a classification of four types of innovation which may be affected by different patterns of collaboration at the level of the firm. The fourfold classification allows for much greater nuance in the explanation of how different forms of firm partnerships may affect different types of innovation. Secondly, rather than classifying firms according to their innovation practices, we use the different interaction linkages of each firm individually as our independent variables of interest, dividing, in turn, DUI-type interactions according to whether they are conducted within the supply-chain or not. Thirdly, we pay specific attention to the often neglected topic of the geographical dimension of the different partnerships of the firm and how they influence innovation. STI and DUI-mode interaction are frequently conducted at different geographical scales and this may significantly affect the capacity of firms to produce different types of innovation. We therefore distinguish between interactions conducted in close geographical proximity, i.e. at the level of a locality or region, and those that are conducted with partners located in distant cities or abroad. Last, but not least, we apply the analysis to a broad sample of firms across different industries in the five largest city-regions of Norway, using a tailored survey specially designed for the purpose of this research. By contrast, earlier studies of the DUI and STI modes in Norway have focused on individual industries in smaller regions (e.g. Isaksen and Karlsen, 2010). The paper is structured into five further sections. In the theoretical section following this introduction, we briefly look at the role of the sources of knowledge and innovation, focusing later on the geography of STI and DUI-modes of innovation. We then present the case and describe the data in Section 3. The following section deals with the empirical analysis linking partner types with innovation outcomes. Section 5 examines the geographical dimension of partnerships and how it is related to innovation. The conclusions and some indications for future research are presented in Section 6.

In this paper we have put Jensen et al.’s (2007) idea that both DUI industrial type and STI scientific type relationships are basic sources for the innovative capacity of firms to the test. We have examined this theory using a sample of 1604 Norwegian firms with more than 10 employees. We consider four different categories of innovation and distinguish between DUI generally formal types of interaction within the supply-chain and those outside the supply-chain, usually of a more informal nature. We have also paid special attention to the geographical dimension of the interactions, differentiating between interactions conducted locally and those at a distance. The results of the analysis confirm that, in the case of Norway, engagement with external agents is closely related to firm innovation. Firms which engage in collaboration with external agents tend to be more innovative than firms that rely on their own resources for innovation. The analysis also validates the hypothesis that both STI and DUI-modes of interaction matter for innovation. However, not all DUI-modes of interaction matter in the same way. Whereas interaction with suppliers tends to promote greater levels of product and process innovation, both of the incremental and radical type, and interaction with customers is particularly beneficial for product innovation, collaboration with competitors has a detrimental effect on the propensity of firms to innovate and partnerships within the same conglomerate only matter for incremental product innovation. The introduction of the geographical component also yields interesting results. Interaction with local agents, by and large, tends to have very little impact on raising a firm's innovation potential. The main exception is STI-type interaction with local universities. Interacting at a distance, however, makes a significant difference for the innovation potential of Norwegian firms. Firms which have established links with extra-regional universities, research centres and consultancies and, in particular, with suppliers and customers outside the region have seen their innovation potential increase radically in virtually all types of innovation. The results for Norwegian firms challenge some long held beliefs about where firms get their innovative capacity. Although it is true that both STI- and DUI-modes of interaction matter, it seems that it is the collaboration of a more formal type that makes all the difference. In our survey we have found significant evidence of interaction of the informal type, such as interaction with competitors and with customers within the region. Interaction which, according to the literature, simply happens because ‘something is in the air’ or as a result of ‘being there’, of sharing the same geographical location (Gertler, 1995). However, there is little indication in the results that this form of interaction and the tacit knowledge it generates leads to substantially higher innovation by Norwegian firms. Excessive cognitive or organised proximity among Norwegian agents in what are relatively small and self-contained city-regions may be detrimental to innovation, with repeated exchanges not leading to the generation of knowledge which can be used and transformed into innovation by local firms (Boschma, 2005 and Torre and Rallet, 2005). Too much interaction with local competitors may lead to lock-in and therefore even hamper innovation, in clear contrast with one of the key ideas on which the literature on industrial districts was based. The heterogeneity among agents is what matters for innovation and such heterogeneity is more common at a distance than in close geographical proximity (Srholec and Verspagen, 2008). Firms are more likely to innovate when they purposely look for partners which may provide knowledge that can then be easily transformed into new ideas. And this is regardless of whether the partners are STI-type partners (mainly universities) or DUI partners within the supply-chain. The most important factor is that these partners have to be able to offer the new knowledge that the firms need and this is achieved, in opposition with the theories of agglomeration, regional innovation systems, and local buzz, by searching for specific partners which may not only be at a considerable cognitive distance from the firms involved, but also at a considerable geographical distance. Overall, this research provides a few answers but raises a whole raft of new questions regarding the role of clusters, tacit knowledge and policy in Norway. It also calls for more in-depth analyses of how collaborations by what are generally relatively small firms emerge with distant partners. Looking into these questions will give us a clearer understanding of what seems a more complex panorama about the sources of firm innovation in Norway than the existing literature would have led us to believe.