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Thus, secondly, the firm level turns out to be important. In this respect, the analyses focus on the spatial dimension of firm related decisions. The literature of the geography of innovation relies on the idea that short spatial distances are beneficial for innovation due to the necessity of close interpersonal relationships and frequent face-to-face contacts. Both are necessary for the transfer of tacit knowledge. Many studies claim that this kind of knowledge is much more valuable in comparison to codified knowledge, given that innovation processes tends to base more on the transfer of external (new) knowledge in comparison to in-house development (Zucker et al. 1994;
Morone & Taylor 2010).
This reasoning is challenged in several ways. As to the spatial implications Boschma (2005) puts forward the idea that several dimensions of proximity are relevant for collaboration, e.g. cognitive and social proximity. As to geographical proximity for analytical purposes it is necessary to isolate it from the other dimensions of proximity.
Thus, only distance matters and this describes a situation where pure local knowledge externalities arise without any form of interaction or cooperation between local entities.
As to empirical research it turns out that the isolation of pure spatial proximity makes no sense.
Boschma concludes that geographical proximity per se cannot be seen as neither a sufficient nor a necessary condition for the exchange of tacit (and all the more codified) knowledge. It is not sufficient because of other complementary forms of proximity like social and cognitive proximity. It is not necessary because of modern forms of communication, e.g. E-mail, Skype, videoconferencing and high personal mobility.
In addition, geographical proximity may cause a lock-in effect. So, spatial concentration of industries with strong ties, close networks and permanent collaboration may very well lead to a myopic view as to the inherently open, unknown and uncertain process of innovation. If this is true (geographical) proximity may cause a negative influence on innovation. A possible solution could be a mixture of local and extra-local linkages (local buzz and global pipelines).
Projekt KompNet2011 Erfolgsfaktoren regionaler Innovationsnetze As to innovation most of the authors agree that the transfer of tacit knowledge is important. But this knowledge transfer predominantly is related to cooperation, i.e.
bases on intended interactions of firms. From this point of view pure spill-over of tacit knowledge is a phenomenon contradictory in itself. This argument corroborates the idea to focus on the cooperation and collaboration behavior of firms. Therefore, we found our analysis on the idea that these – in addition to the innovation capabilities internal to a firm – are the fundamentals of innovation at the firm level.
But collaboration in itself is a vague concept, either. Various forms of collaboration and different types of collaboration partners exist and in addition the intensity of transfer channels fluctuates.
The notion of innovation itself adds to these ambiguities with respect to different forms of innovation and their relevance. Product and process innovations are not very well defined concepts. A basic problem is that it is very difficult to define the degree of innovation founding on measurable criteria. Thus it remains an open question whether the term innovation refers to a marginal improvement or to a block-buster global scale market innovation. Even the Oslo-manual does not solve this problem. Furthermore, organizational, marketing and financial innovations have to be considered.
The relationships between the three aspects of innovation, collaboration and geographical distance have to be disentangled in order to analyze the spatial dimension of innovation so much discussed in the literature. A first step is to separate the three basic linkages of first, innovation and collaboration, second, innovation and physical distance and third, collaboration and geographical proximity. Chart 1 illustrates this reasoning.
A number of studies deal with the impact of cooperation on firms´ innovative activities.
Robin and Schubert (2010) use the data set of the CIS41 survey 2002-2004 and find positive effects of cooperation on product and process innovation. Their paper focuses on formal collaboration between firms and public research institutions and relates to France and Germany. Their results confirm the findings of Mohnen et al. (2007), Belderbos et al. (2004), Nieto and Santamaria (2007). In addition Antonelli and Fassio (2011) reveal a positive impact of vertical knowledge flows on process innovations and horizontal knowledge flows on product innovation. Unfortunately these papers do not consider the influence of geographical distance.
Several authors deal with the influence of geographical distance on innovation. In his seminal article Jaffe (1989) using patents tries to shed light on the meaning of geographical proximity. He relies on patents assigned to firms as an indicator of innovation and relates this to industry R&D and university research at the state level in the US. His outcome is that there is only weak evidence of spillovers from university research within the state.
Fourth Community Innovation Survey (CIS4) of the European Union.
Projekt KompNet2011 Erfolgsfaktoren regionaler Innovationsnetze In general as to the influence of distance previous studies arrive to different outcomes.
The maximum geographical distance of knowledge spillovers varies between at least 75 miles (Anselin et al. 2000), 300 km (Bottazi & Peri 2003) and up to 400 km (Greunz 2005). Most of these spillover-type studies link some indicator of innovation and some measure of distance but fail to consider the mechanisms of knowledge transfer. That means they do not model the form of collaboration resulting in innovation.
Based on data of the 6th Framework Program of the European Union concerning R&D cooperation Autant-Bernard et al. (2007) show that geographical distance plays no role, at least at the European level. They conclude that geographical distance can no longer be considered as the main determinant of collaboration. Instead social distance (network effects) matters. Interestingly this outcome does not hold at the national level.
Relying on a subset of 75 French firms geographical and network effects both influence firms´ decision to cooperate. Here local clustering turns out to be important as to the probability of R&D cooperation.
The spatial dimension and different types of collaboration play a dominant role in Isaksen and Onsagers (2010) article as to knowledge-intensive industries in Norway.
Their sample consists of 1380 firms and they find that with regard to the firms´ innovation partners 20-30 percent are located in spatial proximity (municipality or neighboring municipalities), 40-60 percent are extra-local networks within Norway, and 20-26 percent show an international reach. As to innovation – contradicting conventional reasoning - they reveal that firms in small urban regions and rural regions exhibit larger product and process innovation rates in comparison to large urban regions. But their descriptive analysis does not tackle the question of any links between innovation rates and reach of cooperation. According to their empirical results - 32.6 percent of the firms in small urban regions (10.000-199.000 inhabitants) find collaboration partners in their own local area compared to 19.6 percent in rural regions and 23.3 percent in large urban areas - their seems to be no link between innovativeness and regional reach of collaboration.
De Jong and Freel (2010) explore the geographical distance of innovation collaborations in Dutch high tech small firms. They selected 316 firms that successfully collaborated for innovation (i.e. had new technology-based products in the past three years). As dependent variable they use the geographical distance. About 72 percent of partners were within 150 km and the median distance to partners was 82 km.
Projekt KompNet2011 Erfolgsfaktoren regionaler Innovationsnetze Furthermore, nearly 79 percent of partners were located in the Netherlands. As to the interdependence of innovation and reach of collaboration they do not consider differences with regard to innovation performance (all of the firms of their sample are innovators) but conclude that geographical distance per se has no influence and can be compensated by other forms of proximity.
Drejer and Vinding (2007) concentrate on the propensity of innovative firms to collaborate across geographical distance in two regions of Denmark. They distinguish regional, national and international reach of collaboration. 32.6 percent of the collaboration partners are located in the region, 35.4 percent on the national level and
32.0 percent abroad (Drejer & Vinding 2007). Thus, their data do not point to a clear spatial profile of collaboration. But as to firms in the two regions of East Jutland and North Jutland there are significant differences with regard to the location of their collaboration partners. They conclude that this difference is due to the peripheral and less developed situation in North Jutland.
The spatial reach of successful knowledge transfer is one hypothesis tested by Cummings and Teng (2003). Their survey is based on US high-technology companies with sales greater than US $ 10 million and includes sixty-nine usable responses. Their dependent variable is transfer success and is measured using a 22-item scale that includes a broad range of aspects to provide a reliable measure of transfer success.
The spatial distance is measured using the number of miles between the cooperation partners. Their sample shows a mean of 1433 miles (Cummings & Teng 2003). An interesting outcome is that the spatial distance variable has no significant influence and this result holds as to different specifications of their regression analysis.
Fritsch (2000) refers to the manufacturing sector in the three German regions: Baden, Saxony and Hanover-Brunswick-Göttingen. His survey studies the propensity of firms to cooperate with customers, suppliers, other firms and public research institutions. The dependent variables of his regression models are the existence and the number of cooperative relations. There are significant differences as to the cooperation behavior in his three regions, confirming the idea that the spatial reach of cooperation depends on characteristics of the region at hand. Furthermore, about 30 percent of cooperative links with customers and suppliers are located in the same region. As to other firms (i.e. competitors) nearly 50 percent of all cooperative relationships refer to the regional level and about 55 percent of the cooperative links with public research institutes are Projekt KompNet2011 Erfolgsfaktoren regionaler Innovationsnetze regional collaborations. He concludes that there is a high importance of geographical proximity and that this is especially true as to links with public research institutions.
With regard to collaboration with suppliers and customers spatial proximity turns out to be much less important. Overall, the influence of the spatial reach of collaboration on the innovation success remains open. At the level of the three regions under scrutiny the highest propensity to cooperate locally was found in Saxony but the firms in Baden are leading with regard to innovation.
Krätke‟s (2010) survey for the metropolitan region of Hanover-Brunswick-Göttingen bases on 1138 regional economic actors (453 public research establishments, 613 firms and 72 other establishments). The survey distinguishes different forms of collaboration as to intensity from formal collaboration (high intensity) to education and qualification (low intensity). His outcomes are as follows: 34 percent of all network collaborations are regional links, 43 percent have partners in the national economic territory of Germany and international connections have a share of 23 percent.