Cognitive proximity

People’s mental models and knowledge bases differ as they “see, perceive, interprete and evaluate the world differently” (Nooteboom, 2000b: 71). The concept of cognitive proximity builds upon shared mental models and areas of knowledge, as well as sufficient absorptive

44 In regard to weak ties, the gatekeeper literature emphasizes the importance of individuals, who take over an important role in connecting otherwise very loosely tied or even disconnected parts of knowledge net-works. Also, they link their group or organization to the external environment (e.g. Tushman & Katz, 1980;

Giuliani, 2011; Graf, 2011; Kauffeld-Monz & Fritsch, 2013).

capacity as essential requirements for effective communication and, in turn, successful knowledge interaction and learning.⁴⁵ It relates to closeness of cognitive repertoires and overlap of knowledge bases, respectively, on multiple levels; the inter-personal and the inter-organizational level (Nooteboom, 2000b; Thune, 2009).

For successful knowledge interaction and interactive learning, the knowledge bases and competencies of actors should be close enough in order to detect, understand, absorb and exploit the new knowledge successfully (Boschma, 2005).⁴⁶ Cohen and Levinthal (1990) have underlined that “learning is cumulative, and learning performance is greatest when the object of learning is related to what is already known” (Cohen & Levinthal, 1990: 131).

If the receiver’s knowledge base and absorptive capacity, respectively, are not sufficient, search and assimilation costs for the required new knowledge will be too high.⁴⁷ Thus, a minimum level of relevant pre-existing knowledge is required in order to deal with the exist-ing knowledge gap successfully (Boschma, 2005). Consequently, firms often seek to build interactive ties to actors with similar references and knowledge bases, for example, in communities of practice (Nooteboom, 2000a; Petruzzelli et al., 2007).⁴⁸

Box 4: Technological proximity

Technological proximity is related to cognitive proximity and refers to the similarities between firms’ technological and scientific knowledge. Furthermore, it concerns to what extent companies resemble in “what they produce and/or how they produce it” (Thune, 2009: 9). Knoben and Oerlemans (2006) have distinguished that “cognitive proximity is a much broader concept that refers to the extent to which actors can communicate efficiently, whereas technological proximity refers to the extent to which actors can actually learn from

45 Examples of potentially shared or related knowledge bases between actors include factual knowledge, organizational culture, language, theories and experiences (Thune, 2009).

46 Furthermore, Capello (2009) has measured cognitive proximity in terms of openness to cooperation and new opportunities, as well as needs of market interactions.

47 Absorptive capacity refers to an actor’s ability and capability to identify, absorb, adapt and exploit externally produced and heterogeneous knowledge (Cohen & Levinthal, 1989). It is influenced by actor’s ability and efforts, referred to as inventive capacity, for example, in terms of internal R&D activities, to build prior knowledge bases and expertise inside the organization (Lichtenthaler, 2001). Actors with relevant prior knowledge (i.e. technical and market competencies) are more likely to assimilate new complementary ex-ternal knowledge and exploit it effectively in terms of learning and innovation. To put it differently, what can be learned is affected by what is already known (Cohen & Levinthal, 1990; Revilla et al., 2005).

48 The concept of related variety, often underlined in regional growth theory, also stresses the importance of shared and complementary knowledge bases and competences among different actors and industries in a region. It ensures that some degree of cognitive proximity exists among diverse regional economic actors and industries to enable effective communication, learning, and novel knowledge combination. In contrast, unrelated variety refers to economically not related, disconnected sectors and economic actors in a region (Nooteboom, 2000a; Frenken et al., 2007).

each other” (Knoben & Oerlemans, 2006: 78). Similarity in technological knowledge does not point to technologies themselves, but to the knowledge actors posses about them.

Thus, learning and anticipation of technological developments increases with augmenting technological proximity (Knoben & Oerlemans, 2006). However, cognitive proximity and technological proximity are predominantly used synonymously in the literature, for example, in defining cognitive proximity as ”degree of technological overlap” (Nooteboom et al., 2007: 1017).

However, too much cognitive proximity may reduce the ability for learning and innovation.

Boschma (2005), among others, has identified three reasons why too much technological overlap should be avoided. Firstly, too much compatibility of cognitive repertoires may lead to cognitive lock-in as organizational routines may reduce the awareness and openess for new technology and market opportunities. The creation of new knowledge usually requires different, but complementary knowledge. Secondly, new dissimilar knowledge sources are typically associated with increasing novelty value of knowledge and may provide sources for new knowledge and knowledge re-combinations. Thus, a certain cognitive distance should be maintained to enable interactive learning.⁴⁹ Thirdly, strong cognitive proximity may increase the risk for unintended knowledge spillovers. Cognitively proximate actors, for example, direct competitiors, are more capable of absorbing involuntary knowledge spillovers and exploiting them to their benefit (Boschma, 2005; Nooteboom et al., 2007).

Nonetheless, too much dissimilarity of knowledge bears the risk of failure in creating an effective common understanding and in the application of external knowledge.⁵⁰ Consequently, a balanced level of shared understanding and knowledge diversity is necessary for learning to occur at all. In other words, cognitive proximity has a positive influence on interactive learning to a certain threshold. Beyond this point, cognitive proximity may reduce the potential for learning. Thus, very proximate as well as very distant actors are unlikely to expect high benefits from cooperation in innovation-related activities. Accordingly, the optimal cognitive distance is reached when the knowledge bases of actors have similar elements that create sufficient comprehension, but also different elements and complementary capabilities that enable new combinations of knowledge and, in turn, interactive learning. As a consequence, the relation between cognitive proximity

49 Bercovitz and Feldman (2011) have shown that multi-disciplinary teams composed of researchers of uni-versities, other research institutions and companies are more effective generating successful research commercialization outcomes (e.g. patents, licenses, and royalties) and, thus, stress the importance of knowledge diversity in cases of “truly novel combinations” (Bercovitz & Feldman, 2011: 81).

50 Too much cognitive dissimilarity may also reduce the probability of a joint vision and identity, as Grabher (2004) has highlighted in the case of formally composed advertising project teams.

and a firm’s innovation performance is also characterized by an inverted U-shaped relationship (see Figure 6), similar to social proximity (Boschma, 2005; Menzel, 2015).⁵¹ As Nooteboom (2000a) has stated “a tradeoff needs to be made between cognitive distance, for the sake of novelty, and cognitive proximity, for the sake of efficient absorption.

Information is useless if it is not new, but it is also useless if it is so new that it cannot be understood” (Nooteboom, 2000a: 153).⁵²

Figure 6: Optimal cognitive distance

Source: Nooteboom et al. (2007, p. 1018)

Overall, cognitive proximity is regarded as a essential criterion for knowledge interaction and, in fact, the creation of knowledge and learning. A minimum level of shared cognition is a fundamental condition for effective communication and knowledge interaction to occur.

Also, it is the only type of proximity that actually provides the potential to create novel ideas

51 In this respect, Huber (2012) has underlined the distinct interplay of four different sub-types of cognitive proximity; technical language, the way of thinking, know-how and know-what. Accordingly, strong similarity concerning technical knowledge appears important for effective communication, whereas higher levels of dissimilarity of the three other sub-dimensions are more beneficial to learn new things.

52 Research shows diverging industry-specific applications of balancing the most effective degree of cognitive proximity. For instance, Grabher (2004) has found that core team composition and interaction in software project ecologies are geared towards reducing cognitive distance and cohesion. In contrast, project organ-izing in advertising ecologies rather is aimed at promoting cognitive distance and rivalry in order to trigger creativity. Also, the complexity of technological knowledge influences its transferability. Less complex tech-nologies require less mutually shared knowledge, while very complex techtech-nologies demand for highly simi-lar knowledge bases (Menzel, 2015).

and technologies based on the sharing of knowledge. Consequently, Boschma (2005), among many other scholars, has underlined that it takes over an prominent role within the proximity framework.