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The study explores innovation practices in a virtual organization model in the field of biotechnology from a spatial perspective and demonstrates how an online-based biotech research network turns out as knowledge architect among various individuals, research centers, and universities. The study is theoretically based on cluster research revealing that, in the past decades, biotech R&D cooperation was typically organized in specialized agglomerations (Link & Rees, 1990) consisting of strong local ties (Audretsch & Stephan, 1996), top universities (Niosi & Bas, 2001), and local political and institutional embeddedness (Kaiser, 2008). Moreover temporary external linkages (Torre, 2008) served as ´global pipelines` supporting innovations (Owen-Smith & Powell, 2004; Bathelt, Maskell, & Malmberg, 2002), and avoiding lock-in effects (Grabher, 1993) and overembeddedness (Uzzi, 1997).
However, in recent years, spatially rather unstable and de-territorialized organizations such as project networks (Sydow & Staber, 2002) and project ecologies (Grabher, 2002, 2004) have been studied through network approaches. The fact that geographical proximity is not necessarily a precondition for successful knowledge transfer (Gallie, 2009) and that creation of knowledge is apparently possible through, often spatially disembedded, communities of practice (Brown & Duguid, 1991; Lave & Wenger, 1991) and through virtual communities of practice (Dube, Bourhis, & Jacob, 2005) raised strong interest to geographers, exploring economic interaction and the innovative and creative potential of communities in newly emerging space (Amin & Roberts, 2008). Most recently software’s ´open source`, ´permanently beta` (Neff & Stark, 2004), and the notions of ´open-` and ´user driven innovation` (Chesbrough, 2003; von Hippel, 1988, 1987; Hienerth, 2006) have been systemized into different organizational modes and user-categories distinguished by knowledge types and by behavioral, social, and geographical patterns such as physical and relational distance (Grabher, Ibert, & Flohr, 2008).
One of the latest movements for open innovation models are: the introduction of ´open source biotechnology` concepts (Hope, 2007; Maurer, 2008; Munos, 2006) and advanced ideas on the integration of physicians and patients into drug development processes (Demonaco, Ali, & von Hippel, 2006; Smits & Boon, 2008). Computational biotechnology in particular exposes high potential for open innovation thanks to analogies with software programming (Rai, 2005). These approaches appear as promising new business models but their spatial patterns, however, have so far basically been disregarded. Web 2.0 based interactions have transformed communication patterns and have created a new space which requires to be considered for practically all current and future business models. The study is an attempt to investigate an open innovation model in the field of biotechnology through geographical perspective by applying cluster theory.