Economic Systems Research, Vol. 14, No. 4, 2002
Reaping the Fruits of Science: Comparing Exploitations of a Scienti® c Breakthrough in European Innovation Systems
FINN VALENTIN & RASMUS LUND JENSEN
A bstract This paper is an attempt to unpack the emergence and dynamics of sciencebased technologies in conceptual forms that allow us to understand better when and how the social and economic organization of search and problem-solving matters. The evolution over two decades of a speci® c science-based technology is mapped with data from its 192 patents. For the ® ve European countries generating the majority of patents, we identify the host organizations of all 275 inventors involved in the R&D behind the patents. Using network analysis we then map the evolution of separate innovation systems and their structural and evolutionary characteristics. The best performing system combines a cumulative pattern with frequent and shifting connections to non-system R&D partners while maintaining a small core of almost omnipresent inventor-organizations. The role of multinational corporations in orchestrating innovation systems is apparent. Keywords: Innovation systems; science- technology dynamics; search costs; biotechnology
1. Introduction The ability to create and apply technological knowledge has become recognized as a key determinant of competitiveness and growth (Fagerberg, 2001). This ability, furthermore, is no longer understood as a function merely of internal characteristics of organizations. Not only are externalities important (Romer, 1986), so is the way they become accessible for individual actors (Audretsch & Feldman, 1996; Feldman, 1999). Accessibility, in turn, is moulded largely by inter-organizational arrangements, as we learn from the literature on innovation systems (IS), whether these arrangements are de® ned within regional, national, sectoral or technological delimitations (Edquist, 1997). Various approaches have been taken in the literature on how the organization of an IS mediates externalities into the technological performance of its ® rms. Thus, one approach has focused on speci® c types of vertical or horizontal con® gurations of actors, such as user- producer interaction (Lundvall, 1992), or the universitylocal ® rms nexus (Saxenian, 1994; Varga, 2000). Policy-makers have elevated some Finn Valentin and Rasmus Lund Jensen, Copenhagen Business School, Department of Industrial Economics and Strategy, Solbjergvej 3, 2000 F, Copenhagen, Denmark. E-mail: valentin@cbs.dk ISSN 0953-5314 print; 1469-5758 online/02/040363-26 ©2002 The International Input- Output Association
DOI: 10.1080/0953531022000024842
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of these con® gurations to the status of policy models, e.g. for `science-based regions’ or `triple helix’ constructs. While the focus on speci® c organizational con® gurations signi® cantly advanced our understanding of ISs, it does not square easily with other strains of innovation research that brought out the heterogeneous nature of R&D with increasing clarity. Cognitive forms of R&D problem solving diþ er signi® cantly, not only across classical juxtapositions of science- versus learning-based technologies (Rosenberg, 1982). Even within science-based technologies there is diþ erentiation, with profound implications for the design of science and university policies (Meyer-Krahmer & Schmoch, 1998; Valentin, 2000). As a consequence, a corresponding variation is observed in the amount and the kind of externalities exploited in diþ erent types of ® rms (Klevorick et al., 1995, Pavitt, 1984). This cognitive heterogeneity of R&D translates into the kinds of requisite variations in organization that have been documented in a number of studies e.g. (Iansiti & West, 1999). Any single type of organizational con® guration may be essential for speci® c types of R&D and unimportant for others. The general enthusiasm in IS studies for `thick organization’ needs the challenge from comparative approaches focusing on variations in R&D cognition and their requisite organizational diþ erences. One such comparative approach is the concept of technology systems (Carlsson & Stankiewicz, 1991; Carlsson, 1997) which suggests a set of comparative dimensions to bring out diþ erences in the knowledge- organization nexus in diþ erent technology systems. That is the nexus pursued in this paper, which is an attempt to extend the technology system approach in three interrelated directions. (1) Specifying further the cognitive contingencies of R&D problem-solving as they bear on inter-organizational linkages between actors. The paper attempts to unpack the emergence and dynamics of science-based technologies in conceptual forms that allow us to understand better when and how the social and economic organization of search and problem-solving matters. Empirically, we examine if such organizational diþ erences are indeed related to the eþ ectiveness and performance in the development of Science and Technologies (S&T) in four diþ erent innovation systems evolving, and competing, within the same science-based technology. (2) Following the evolution of a speci® c S&T ® eld over two decades to identify shifts in interorganizational arrangements required to maintain eþ ectiveness in R&D. (3) Exploring the possibilities of using and extending patent data to map cognitive shifts and their eþ ects on the organization of innovation systems. 2. The Role of System Organization in Science-based Technologies 2.1 Time-patterns and Search Costs of Inventive Activity Breakthroughs in the science-base of technologies give rise to increasing inventive activity in a time-pattern that has been observed across diverse technologies. Grupp (1992, 1998) suggests a model with eight sequences that we will simplify into three main stages. (1) `The stage of breakthrough’ opens with radical advances in research spurring a rise in scienti® c activity (as re¯ ected in the level of publication). Early sporadic attempts at technological exploitation follow, indicated by a ® rst round of patenting. (2) In the second phase, rather than continuing their initial steep increase, research and technology developments (patents) stabilize at the
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activity plateau achieved during the breakthrough. Lacunae in scienti® c insights and technologies on the one hand hold back activities, but also help to reorient agendas, bringing about a gradual, latent maturation of the potentials of the science and technology base. This phaseÐ which may last from a few years to a decade or moreÐ will be referred to as `stagnation and reorientation’ . (3) The third stage of `technology take-oþ ’ shows steep increases in patenting, followed by even steeper increases in production and sales. Increases in scienti® c activityÐ although with lower growth-rates than seen for patenting and productionÐ underpin this exploitation of matured opportunities. To become part of science-based economic growth, what matters is having key actorsÐ research organizations and companiesÐ attractively positioned during takeoþ and growth in Stage 3. The interesting question concerns what role innovation systems and their organization may play in this context. To answer these questions we need to understand what shapes the three-stage pattern. Understanding advances in S&T in terms of their eþ ects on search costs is one way of moving towards answers. A search costs approach departs from the tradition in S&T studies where scienti® c breakthroughs are conceptualized primarily in terms of leaps in insight relative to previously existing knowledge (e.g. Hurley, 1997). Instead, the signi® cance of a breakthrough is conceptualized by its eþ ect of reducing search costs within a broad scope of other subsequent R&D agendas, only few of which may have been anticipated at the point of discovery (Nelson, 1959; Arrow, 1962; David et al., 1994). From this perspective, breakthroughs do not have their signi® cance derived from their level of intellectual originality and creativity per se, but from the improvement of search economies oþ ered to subsequent R&D. A search cost approach becomes particularly useful when we conceptualize speci® c scienti® c insights and technologies as bundles of constituent components. 2.2. The Bundled Nature of Technology and Science Science and technology are two separate (but interlinked) knowledge systems. They share, however, the fundamental characteristic of being systemic in the sense that their constituent parts become useful, but not as separate generic elements. Taking technologies as our example, they become functional in the form of bundles of operands, combined into functional con® gurations, such as aeroplanes or pencils (Stankiewicz, 2000). Consequently, a notable advance in any one sub-technology can be exploited only if other complementary technologies within the same bundle performÐ or can readily be made to performÐ in alignment with the initial advance. Performance de® ciencies in complementary technologies requiring such adjustments will be referred to as `alignment gaps’ .1 This systemic quality of technologies has a profound impact on their evolution (Ayres, 1994; Rosenberg, 1994) The above three-stage pattern of S&T dynamics is shaped by the way inventive activity responds to alignment gaps. During the breakthrough, complementary technologies (or research tools and concepts) are highly de® cient or may be completely lacking, and technologies are tried out on a highly experimental basis. Inventions, as well as research, are concerned primarily with understanding the implications of the breakthrough, not least in terms of what complementary insights and technologies will be required for its eþ ective exploitation. In Stage 2, the plateau of moderate inventive activity is, in fact, the level where two opposite forces are balanced. On the one hand, the promise of advances
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associated with the breakthrough keeps mobilizing research and experimental designs, on the other hand, search costs are prohibitively high. In this stage, search is as much concerned with understanding targets as with ® nding solutions. High uncertainty about what the ® nal bundle of insights and technologies will eventually look like means that scientists and inventors lack critical information on what targets to pursue in research and in experimental design. By way of example, R&D in optical communication was spurred in the late 1950s by the invention of laser technology (the key science background of which, in turn, goes back to the possibility of stimulated light emission theorized by Einstein in 1916). The implications of lasers for potential communication technologies were realized almost immediately. R&D, however, driven over the next two decades by this invention, shifted the locus of (attempted) exploitation across a highly diverse set of issues, attracted by (expected) least alignment gaps in complementary technologies in a typical Stage 2 fashion (Ausubel & Langford, 1987; Whinnery, 1987; Harbison & Nahory, 1997; Grupp, 1998; Hecht, 1999). The S&T dynamics of lasers is merely an example of the general pattern, repeatedly documented in historical studies, of Stage 2 R&D gravitating towards ® elds of least alignment gaps, which later fail to converge into an operative technology bundle. As usable complementary technologies begin to emerge, search costs for both solutions and targets begin to decline. The take-oþ stage begins when they are reduced to the level where R&D-uncertainty becomes acceptable for early movers. Reduced uncertainty and search costs allow R&D activities to increase. R&D aimed at understanding, testing and stabilizing complementary technologies is now suYciently promising to be undertaken on a large scale. In this sense R&D now addresses an opportunity space of increasing complexity and heterogeneity (Orsenigo et al., 2001). 2.3. The Role of Organization So far, search costs have been considered only as they are determined by alignment gaps as de® ned above, i.e. derived from lacunae in science and technologies in terms of de® cient performance, functionality or understanding. The search costs experienced by individual inventors, however, may vary as a function of the organization of their relationships. Further coordination, co-specialization and collaboration may reinforce small initial search advantages, experienced in speci® c relationships. In this way, search costs for solving one and the same R&D problem may come to diþ er signi® cantly between actors as some inventors achieve advantageous access to insights, skills, targets, or other enabling conditions made available to them by other actors. We shall refer to this type of enablement as `advantageous search positions’ , emphasizing the positional basis for advantages of this type. Thus, outside the scope of analysis of the present paper, further non-positional advantages may accrue to inventors on the basis of their internal organization and prioritization of some R&D issues above others. Attentiveness to absorptive capacity is one such aspect of company internal R&D that has been shown to generate signi® cant search advantages (Cohen & Levinthal, 1990; Stankiewicz, 1997). The argument of the present paper is focused on the positional advantages derived from inter-organizational aspects of inventor relationships, such as frequency, repetition, and diversity of contacts, past experience of sharing information or of collaboration etc. This organizational dimension, we suggest, varies in importance over the three