Page - (000279) - in Knowledge and Networks

276 parallel and rival experimentation are more likely to generate variations of tech- niques and solutions that would be impossible within a single firm because of the common vision and corporate coherence it needs. This variety increases the oppor- tunities for each firm to identify and imitate successful practices by attentively observing their competitors (Malmberg & Maskell, 2002; Malmberg & Power, 2005). There are various mechanisms to promote observation and imitation. One is learning-by-hiring (Song, Almeida, & Wu, 2003), another is the adoption of new information and ideas from the “local buzz” within a communication ecology (Bathelt, Malmberg, & Maskell, 2004). Cluster structures favor competition and rivalry in these ways because competitors operate under the same environmental conditions, meaning that none can credibly claim any advantages—or excuse lag- gardness—deriving from external factors (Porter, 1998). Consequently, competition for innovation focuses purely on a firm’s ability to develop new solutions and launch them on the market. Geographic proximity grants many competitors increased vis- ibility and thus a greater opportunity to imitate new solutions more quickly than is likely for a spatially isolated firm. There was once a time when urban variety and density were considered the drivers of imitation and the recombination of existing knowledge in other sectors or functional areas and when the city was seen as the driver of economic innovation (on both counts see Jacobs, 1969). More recently, however, proponents of cluster approaches (Malmberg & Maskell, 2002; Porter, 1998) note that rivalry, observation, and imitation under the same local underlying conditions can also be the source of innovation for local production systems outside cities and urban regions. Unlike the concept of the industrial district, which high- lights interactional collaboration, the concept underlying cluster approaches bases learning on noninteractional rivalry. In addition, rival learning can explain why firms in clusters enter into so few formal cooperations (Malmberg & Maskell, 2002; Angelov, 2006). Organized Network Unlike regional clusters, which are often only loosely linked, the organized network focuses on actively coordinated interfirm cooperation. We define an organized net- work as a voluntary and purposive association of members that aligns the multilat- eral collaboration between a finite number of independent organizations with a collectively shared utility (Glückler, 2012). Organized networks serve to generate cooperation gains and external savings. They are an organizational instrument for constantly reinforcing the competitiveness of the individual members (Araujo & Brito, 1997). This networking makes it possible to recombine various kinds of knowledge, something that no individual member would achieve in its entirety (von Hayek, 1945; Inkpen & Tsang, 2005). The tendency to cooperate enables corporate networks to offer a backdrop for cooperative learning; they jointly generate knowl- edge with friendly imitation. To use the advantages of this cooperation jointly, rules and organs through which to implement them are developed by the members as part of their network gover- J. Glückler and I. Hammer