Academic journal article Innovation: Organization & Management

Innovation Systems as Patent Networks: The Netherlands, India and Nanotech

Academic journal article Innovation: Organization & Management

Innovation Systems as Patent Networks: The Netherlands, India and Nanotech

Article excerpt

... there is much more information derivable from the patent documents than just simply their aggregated numbers in a particular year or for a particular firm. (Griliches 1990, p. 1664)

Both academics and policy makers have found the National Innovation Systems (NIS) literature to contribute useful insights. Some, however, believe that the NIS literature (Lundvall 1992; Nelson 1993; Edquist 2004) has become bogged down into case studies of how specific institutions affect innovation in a specific country. As Balzat and Hanusch (2004) argue: there is a need for NIS studies to develop complementary and also quantitative methods in order to generate new insights that are comparable across national borders. In this paper we use data on patents granted by the World Intellectual Property Organization (WIPO), a UN organization, to map innovation systems. Applying for a patent at the WIPO is relatively easy and cheap, and allows the applicant to both apply in relevant markets afterwards, and establish their position vis-à-vis competitors. Rather than taking counts of the number of patents granted, by field, company, region or country, which would meet with all the drawbacks that patents have as an indicator for innovation (Kleinknecht et al. 2002), we use different information that can be drawn from patents.

Patents are grouped into a primary class and secondary classes by patent examiners. Co-classification of a patent in two classes signifies a relation between these classes that is significant from the point of view of knowledge development and thus for studying a knowledge-based innovation system. Using social network analysis, one can map these co-classifications among patent classes and thus characterize a NIS. Such an analysis of a NIS focuses on what nation specific components and relationships in a system, each with their characteristics and attributes (Carlsson et al. 2002), actually produce. It does so in a manner that indicates the relations between knowledge fields as well as, to some degree, the nature of such relations as part of the larger (socio-cognitive) network configuration. In doing so, the results of an analysis of (national) innovation systems becomes amenable for comparison (between nations; Liu & White 2001).

One may argue that this approach ignores the idiosyncracies of national systems, but one may as well argue that such an analysis may enable us to understand these idiosyncracies. In addition, the analysis can focus on regions as well as specific technological fields, which may allow for theoretical integration between NIS, regional innovation systems (Cantner & Graf 2006) and sector innovation systems (Dittrich & Duysters 2007; Storz 2008) where a similar network approach can be adopted. Analysis of industrial production in terms of input-output matrices adopts or could adopt similar methods (Verspagen 1997; Lenocini & Montresor 2000; Lotti & Santarelli 2001).

The empirical analysis of NIS as patent networks may thus open possibilities for theoretical integration of NIS to adjoining fields of academic research. Yet, the main contribution of this paper may perhaps be methodological - as it adds to the repertoire of methods NIS studies use, but also as a different kind of information on patents is used. In addition, policy makers are interested in knowing how knowledge development in an innovation system is interrelated, and thus obtain an understanding of how production structures may evolve in the near future. It might also indicate which policy domains may emerge as important issues. For instance, using social network analysis of the complete set of 3,287 patents granted by the WIPO to Dutch firms and individuals in 2006, we find that biotech, pharmaceutical and chemical technology, with applications in food and medication may be overtaking the traditionally dominant position of electronics/computer technology. Given that these technological fields and their associated industries show high propensities to patent, the dependence of the Dutch NIS on patent law thus increases. …

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