Knowledge Creation in Biotechnology-Related Industries
Modern biotechnology is a knowledge-intensive field and refers to the “application of science and technology to living organisms, as well as parts, products and models thereof, to alter living or non-living materials for the production of knowledge, goods and services” (OECD 2015). It is expected that the application of biotechnology to agriculture, health and industry will result in an emerging “bioeconomy” where biotechnology contributes to a significant share of economic output (OECD 2009). A large number of small biotechnology firms have emerged challenging the innovation strategies of incumbent companies. Today, biotechnology-related industries are highly R&D intensive: pharmaceuticals and biotechnology rank among the highest in terms of business R&D in the EU and world-wide (European Commission 2013, pp. 39-45).
However, not only financial inputs to R&D are relevant for the performance of a complex innovation system (see, for instance, Katz 2006). Organizational aspects, particularly collaborative knowledge creation processes are gaining importance (Hoekman et al. 2009; Reinold et al. 2013). Innovating organizations must interact more actively and purposefully with each other in order to cope with converging technologies and increasing market pressures in a globalizing world. In this changing environment, biotechnology has become a much-noticed industry where formal R&D collaboration with external partners (alliances, project consortia) is a major channel for the exchange of knowledge, as well as a source of new development (Powell et al. 1996; Koput et al. 1997). External sourcing in networks of organizations thus becomes a widely used complement to in-house development. Hereby, mainly two factors, spatial proximity and organizational form, affect the way such networks are used (Owen-Smith and Powell 2004). In local clusters, access to networks with university and public research seems to foster knowledge exchange, while in global networks in addition a central position in corporate networks is important to benefit from collaboration (McKelvey et al. 2003). General affinity towards alliance formation is strongly correlated with the technological breadth of firms (Zhang et al. 2007), but also small biotech start-ups significantly benefit from engaging in alliances: Firms that engage in joint invention activities develop broader capabilities than firms that pursue in-house inventions only (Khoury and Pleggenkuhle-Miles 2011).
Rooted in academic research, biotechnology has entered the pharmaceutical industry (and other industries) developing a new, lean vertical structure: Dedicated biotechnology firms form a specialized layer between the non-profit research sector and large diversified firms (e.g. Cockburn 2004; Stuart et al. 2007; Saviotti and Catherine 2008). To allow a co-ordinated conduct of research into new therapeutic substances or production processes, upstream and downstream collaborations are vital for dedicated biotech firms. The direct link between basic research and product market and the existence of tight collaboration networks between the firms display the lean structure of biotechnology-related industries as compared with other industries like microelectronics.
Collaborative knowledge creation has become so obvious in this industry that some authors have come up with the notion of the interfirm (e.g. Baum and Ingram 2002). In any case, continuous interaction and the mutual exchange of knowledge among organizations lead to the coevolution of firms along joint technological trajectories, creating strong path dependence (Santos 2003; Antonelli 2011; Krafft and Quatraro 2011). Hereby, biotechnology is reported to support an incremental pattern of technological change—at least in the pharmaceutical industry—that builds upon, rather than disrupts, previous drug development heuristics (Hopkins et al. 2007). The high collaboration intensity observed in this industry requires a careful handling of intellectual property: Making implicit knowledge more explicit supports the protection of intellectual property by legal provisions and at the same time makes knowledge more measurable for analytic purposes.
An important way to protect intellectual property is patents—exclusive rights to use a technical invention for a limited period of time in exchange for its detailed public disclosure. Although their supporting or hindering role in innovation is disputed (Shapiro 2001; Roper and Hewitt-Dundas 2015), patents are a well- established innovation indicator of technological knowledge creation and have been widely used in the literature (e.g. Basberg 1987; Griliches 1990). However, since patenting is embedded in the overall firm-specific strategy towards intellectual property, the use of specific indicators derived solely from patents can be misleading (Hall and Bagchi-Sen 2007; Nelson 2009). To support the validity of patent analyses, the combination of patent data with other data, for instance scientific publications, is therefore generally recommended. In any case, a deeper look into bibliographic data provides also an opportunity to measure novelty and the analysis of technological development (Verhoeven et al. 2016).
By and large, biotechnology seems to represent a case where patents reveal a quite accurate picture of the newly created knowledge not only at the industry level but also at the level of firms. First, and consistently with their high intensity of collaboration, pharmaceuticals and biotechnology are among the Top 5 of patentintensive industries (Wajsman et al. 2013). Second, biotechnology patenting is crucial for all firms and patenting trends indicate their facilitating and not stifling role for innovation (Barfield and Calfee 2007; Linton et al. 2008). And finally third, the validity of patents as an indicator for knowledge creation is endorsed by the strong interdependence of patenting and scientific publication in biotechnology. This can be seen not only from the key role of outstanding individuals that are able to link the academic and commercial worlds (Breschi and Catalini 2010) but also from the positive citation impact that academic research receives if it is patented (Magerman et al. 2015).
According to the concept of national innovation systems (Nelson 1993), the innovation performance of a country depends on the functional interplay between several sub-systems: government actors and institutions, academic and industry research, the education system, finance as well as technology transfer institutions. R&D policy is an essential driver of technological development within such innovation systems. Depending on the technology field, successful policy interventions have to be carefully adapted to the specific institutional arrangement and the country-specific demands, as illustrated in a comparison of US and German biotechnology (Giesecke 2000). Hereby, national policies usually focus on R&D, although biotechnology is a “striking example of the disconnect between the location of knowledge creation and its commercial development” (Gittelman 2006, p. 1052): Whereas world-class scientific research in the life sciences is distributed across many countries, the United States leads by far in developing commercial applications. For example, in Austrian biotechnology a particular strength has emerged in the last two decades with regard to academic knowledge production, whereas the corresponding industry is still conceded a niche role as compared with critical masses on a global-scale (Wirth 2013; Gulas et al. 2014). Accordingly, a policy focused on the provision of public research infrastructure must be accompanied with measures to foster regional business performance (Burton and Hicks 2006). Thus, apart from sufficient funding of universities and the R&D system, other instruments like training and education, support for entrepreneurship, the availability of finance as well as changes to taxation systems and intellectual property rights are recommended for Austria in order to bring biotechnology start-ups in the position to engage in international networks (Trippl et al. 2006). At the European level, public support for biotechnology was mainly channelled into supporting the creation of start-ups—thus, to create links between universities and industry, governments made venture capital available and introduced policies to stimulate the creation of university spin-offs (Genet et al. 2012). For Austria, recent patenting trends in the biotechnology-related industry are promising in the context of the actual policy debate how to improve the performance of the industry (Breitfeller et al. 2014).