Facilitating Knowledge Creation and Transfer

Creation and transfer of knowledge as well as the other issues presented below address various aspects of enterprise functioning in a CO, therefore the arguments indicating their significant role in building competitive advantage derive from observations, analyses and considerations regarding these particular factors (and thus different aspects of proximity).

Among the others, social proximity is highly important due to the mechanisms of creating and transferring knowledge. It demonstrates the significant impact of non-economic factors on economic activities carried out by individual or collective entities. In the context of social proximity, these non-economic factors are limited to the relations among actors that form larger entities. In order to acknowledge these relations as an indicator of social proximity, they must involve trust based on at least one of the following: kinship, friendship or past personal experience connecting the analyzed entities (Boschma, 2005a; Czakon, 2010; Heringa et al., 2014; Broekel & Boschma, 2012). At the group level, social proximity may relate to the degree of overlapping network relations among the organization individuals (Boschma et al., 2014) and the network of past and present cooperative bonds among these organizations. The literature indicates that maintaining social proximity enhances learning processes (and thus increases the innovation potential) (Boschma, 2005a; Czakon, 2010) and the mechanisms of tacit knowledge exchange.10 The positive impact of social proximity on the results of cooperation among entities has been extensively described by scholars. Empirical research reveals that networks of social relations built on personal relations resulting from the experience of joint work are distinctively important carriers and transmitters for reciprocal knowledgesharing processes (Breschi & Lissoni, 2009). They also act as a stimulus to more frequent contacts of organizations employing the entities that maintain close social relations (Agrawal et al., 2006). Accordingly, it is only a step away from recognizing personal interactions as a factor positively influencing the innovativeness of enterprises - as the research by Montreal high technology companies has shown, representatives of these sectors strongly linked these both variables (more clearly in the smaller biopharmaceutical sector than the larger aeronautical sector though) (Tremblay et al., 2003). A similar dependence has been indicated in European research on the technological progress of individual EU regions, where social proximity was recognized as one of the determinants of innovative activity (although its impact was defined as moderate) (Paci et al., 2014). In the case of cooperation between Italian enterprises and universities, social proximity was one of the determinants of building the very cooperative relations, effectively opposing the inhibitory tendencies resulting from the large geographical distance that often separated the cooperating units (Guerini et al., 2013). Similarly, an analysis of enterprises operating under strategic alliances showed that although the social proximity of the involved entities facilitated the initiation and implementation of knowledge exchange processes among the partners, this impact was rather limited when compared to the strength of influence exerted by technological proximity (being one of the subtypes of cognitive proximity) and the geographical one (Usai et al., 2017). However, a much more important consequence of social proximity of the enterprises was the fact that such easy interaction and exchange of knowledge with the already known entities led to selfreconstructing cooperation processes affecting not only the entities involved in it, but the entire network in which these entities participated (Usai et ah, 2017).

Improving the process of knowledge production and exchange by creating a stable basis for the flow of tacit knowledge (necessary for proper understanding and application of formal, i.e. codified, knowledge) and pooling other, less standard resources is the consequence of the entities remaining in organizational proximity (Knoben &t Oerlemans, 2006). Organizational proximity is applicable to cluster enterprises that share, e.g. a part of their operating procedures or a specific element of their functioning (e.g. joint purchases from a specific supplier, one sales platform under the umbrella of the cluster/СО, etc.).

Institutional proximity, i.e. the entire external axionormative context in which a given CO is anchored, also plays a crucial role in generating the discussed consequence of cluster cooperation. The phenomenon of organizational proximity acts as a binder - it combines into one, into a relatively coherent whole, ample seemingly distant ideas, values and norms of conduct. In the Italian studies of strategic alliances discussed above (Usai et ah, 2017), institutional proximity had an impact (rather limited though) on cooperation and exchange of knowledge among business partners.

Another dimension that emphasizes the mechanisms of knowledge creation and transfer (including learning processes) is cognitive proximity, which is understood as a similarity of the processes of perceiving, interpreting, understanding and assessing the world (Wuyts et ah, 2005). At the same time, it is an element necessary for the proper functioning of communication processes and knowledge transfer mechanisms as it enables accurate identification, proper interpretation and effective use of new elements in the knowledge system (Cohen & Levinthal, 1990). Both exchange and creation of knowledge are processes that do not take place in an intellectual or mental vacuum, but are based on already existing knowledge systems of cooperating entities. In the process of knowledge exchange (and thus in the learning process), two, partly similar and partly different systems of knowledge and experience are combined, which, supporting each other, strive (in a minimum variant) to supplement their cognitive structures with elements hitherto missing in them, and (in the most complete variant) - to create a new content in response to a problem. However, it is worth remembering that the entities remaining in an active cooperation relation do not accept new elements without previous consideration and modify them in a more or less explicit way, adapting them as closely as possible to the specifics of their own knowledge system. In other words, learning is an emergent process whose effects are always greater than the sum of the elements listed during its course (Tremblay et al., 2003). Therefore, for companies intending to succeed, the knowledge bases of the entities are supposed to be complementary but not the same (Broekel Sc Boschma, 2012) because only such a combination guarantees creativity and effective growth of the involved knowledge systems. Similar conclusions can be drawn from the research of the German R&D sector: to achieve beneficial effects of cooperation under certain projects, it was favorable for the entities to remain in a slight cognitive (technological - the authors used these terms interchangeably) distance (Marek et ah, 2017). Another reason why entities cooperating in the knowledge network should maintain a certain cognitive distance is the possibility of avoiding “lock-in” in finite, routine reality, and thus getting out of the usual patterns of action and too familiar relation paths. “Lock-in” may mean giving up implementation of new technologies or taking advantage of new market opportunities (Boschma, 2005a). By performing a relatively well- known set of activities, an organization may not feel the need to modify them or to abandon them in favor of other, perhaps more effective actions. This phenomenon is referred to in the literature as the “competency trap” (Levitt &c March, 1988). According to Boschma (2005a), only a pool of relatively diverse partners able to find common threads to cooperate guarantees cooperative relations resistant to threats that result from too little cognitive distance. The specific nature of cluster activities makes COs an ideal place to establish cooperation relations with partners that differ from one another, but at the same time perceive many issues in a similar way. Despite the relatively rare attempt of addressing such issues by researchers, their research results and scientific experience indicate the great importance of cognitive proximity for undertaking cooperation, exchange of knowledge and innovative activity (though the results are not entirely clear). Studies run by the Dutch water sector have shown that entities with similar knowledge bases more often reported achieving positive effects of their cooperative activities (Heringa et al., 2014). Similar conclusions were drawn from the analysis of the cooperation of the European nanotechnology sector - joint technological experience and related knowledge systems facilitated cooperation among the sector actors. Nevertheless, what is very important and corresponds to the comments made earlier - the best results were achieved in the cases where technological proximity remained at a moderate level (Cunningham & Werker, 2012). Research on Italian strategic alliances has clearly indicated technological proximity as the factor that most determines the process of inter?organizational exchange of knowledge - this effect increased along with the growing degree of similarity of production profiles and knowledge bases of the partners (therefore, it was most visible among the enterprises representing the same industry) (Usai et al., 2017). A positive impact of technological proximity on the knowledge flow has also been discovered (Aldieri & Vinci, 2016). However, the impact of cognitive/technological proximity on the innovation activity of enterprises appears quite ambiguous. There are some research results which allow to draw a conclusion about the significant impact of cognitive proximity on innovative activity (Paci et ah, 2014), whereas some other findings indicate a lack of influence of this dimension of proximity on enterprise innovativeness (Broekel & Boschma, 2012). Still other studies emphasize that the relationship between cognitive distance and innovation activities of the actors involved in a given relation takes the shape of the inverted letter “U”, thus both the lack of cognitive proximity as well as cognitive proximity at a very high level brings little benefit for innovative activity (Cohendet & Llerena, 1997). It is also worth noting that the cooperation exploiting the existing technologies has been more efficient in the context of technological proximity, while cooperation focused on shifting technological boundaries benefited more from technological distance (Petruzzelli, 2008). Partially shared competences of enterprises located in the same area (and thus remaining in geographical proximity with each other) triggered a greater ability to absorb knowledge in these entities and allowed them to use learning processes more effectively (compared to enterprises with similar competences but different location) (Boschma, 2005a). Considering the level of enterprise innovativeness, it must also be pointed out that in the Dutch aviation sector, the relations with a geographically close partner but remaining in a certain technological distance had a positive impact on the innovation of these entities (Broekel Sc Boschma, 2012). However, an analysis of the renewable energy sector in the United States has shown that although technological proximity was a factor positively influencing the innovativeness of cooperating entities, their geographical distance did not modify this effect in any way. Cultural distance was a much more influencing factor (Guan Sc Yan, 2016).

Short geographical distance, natural for the vast majority of COs, also has an impact on the issues discussed within this set of factors. The significant influence of the consequences of sharing one location on the activity of entities embedded in the specific area has been strongly reflected in the scientific analyses on the role of location in the business and economic spheres. According to Porter (1990), highly localized processes create and consolidate the competitive advantage of the region and the entities operating in it. This idea has become the basis for the emergence of numerous, territorially oriented theories of innovation (just like the previously mentioned “innovative milieu” or “regional innovation system”). The importance of geographical proximity for creating a competitive advantage has also been scrutinized by Jaffe et al. (1993) and Audretsch and Feldman (1996, 2004). In each of these cases, geographical proximity is perceived as a source of privileged position with regard to access to knowledge, its creation and dissemination. Boschma presents this issue in a similar way, noting that enterprises located near knowledge sources obtain more benefits, and the more potential sources of knowledge in a given area, the greater benefits the local agents expect (Boschma, 2005a). Moreover, local companies sharing a relatively similar set of competences related to a specific area of knowledge are more likely to absorb knowledge and learn than companies outside this area. Remaining at a short physical distance brought comparably positive effects for knowledge flow and creation of new patents in Japan (Inoue et al., 2017), the USA and Europe (Aldieri & Vinci, 2016), and cooperation between universities and the local companies in Estonia (Kuttim, 2016) and China (Lin et al., 2015).

 
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