Knowledge management and sharing in collaborative relationships

As already outlined above, CR are characterised by linkages of interaction (Auster, 1992) as well as repeating and enduring exchange of information (Inkpen and Tsang, 2005) shaped by channels of communication (Gulati, 1995) and KS (Gulati and Gargiulo, 1999). They can exists inside and outside the organisation (Roger and Kincaid, 1981).

Similar to the debate of where knowledge resides within the organisation, a debate developed about knowledge in networks residing within the linkages or within the network as a whole. This debate is found among others in research about social capital (Nahapiet and Ghoshal, 1998) outlined further below. Podolny (2001, p.35) states that networks are not only “pipes carrying the stuff of the market;

they are prisms, splitting out and inducing differentiation among actors on at least one side of a market”. Meaning that the relationship as well as the node, being the organisation or the individual, can carry knowledge (Brass et al., 2004). This view is also followed in this work.

Despite to the question of where the resources are stored and how the network partners are intertwined, another important aspect is how knowledge can be accessed, managed and incorporated.

CR can be superior to firm’s ability to create knowledge, when first mover advantage or uncertain environments exist and when there is a need for specialised knowledge and existing routines and directions need to be overcome (Grant and Baden-Fuller, 2004). Furthermore, when companies chose to explore new knowledge, CR can enable knowledge access to a variety of partner resources. New

knowledge that can then be explored due to distinct knowledge bases available. This underlines the possibility for companies to create new combinations of knowledge and explore new knowledge (Arya and Lin, 2007; Shafique, 2013). For the single company networks can offer additional advantages in new knowledge access, as they do not need to build up routines (Grant and Baden-Fuller, 2004) but can build up a KS network (Marabelli and Newell, 2012; Caimo and Lomi, 2014).

In contrast to the possibility to better access knowledge, CR or network relations are inferior in knowledge integration. They cannot develop directions and routines and they might not be able to develop the same amount of capabilities out of the knowledge accessed as the single organisation would be (Grant, 1996a; Grant, 1996b; Zander, 1995; Teece, 2000). Especially, as they need to deal with a high amount of knowledge that is accessed. This also means that network structures are generally inferior using ‘higher-order organizing principles’ (Grant and Baden-Fuller, 2004, p.68) as they have no authority based relationships (Ahuja and Carley, 1999). Knowledge integration and learning is therefore important to be done on the organisational level to sustain the competitive advantage of the single company (Teece, 2000).

Organisations can benefit from using CR for accessing knowledge and being also able to integrate it, therefore the aim orientation of the organisation in CR is essential. When organisations just want to adapt resources to their own resources they acquire resources through exploration. Resources assessing happens through exploitation (March, 1991; Grant and Baden-Fuller, 2004). For both activities the company needs to be able to learn and should have a certain absorptive capacity (Cohen and Levienthal, 1990) as knowing about existing knowledge is important as basis for knowledge exploration and exploitation. Conner and Prahalad (1996, p.477–501) use the term ‘knowledge substitution’ which could also be described as matching old to new knowledge (Berghman et al., 2013).

As networks offer resource exchange benefits as well as KS advantages, organisations in networks might profit from being in collaborations when they are able to use the knowledge that has been shared and match it to their own strategy, vision and aim (Lorenzoni and Baden-Fuller, 1995). The

access to knowledge in collaborations depends very much on the aim that is targeted by its members and by the resource exchange, such as the aim of new market entrance (Danneels, 2008) or developing new business models (Chesbrough, 2010).

Companies in networks can either access and integrate knowledge or just process it to other network partners (Ahuja, 2000) and serve as a KS hub (Lee et al., 2017). The sharing of knowledge between partners is influenced by the knowledge that is wanted to be shared, as explicit knowledge can be shared context independent while tacit knowledge needs to be shared through practise and content relation (Marabelli and Newell, 2012) which requires a high level on interaction, closeness and communication. Therefore, KS activities of single organisations depend very much on the company aim as well as the network aim (Grant and Baden-Fuller, 2004; De Wit and Meyer, 2010). Being able to influence knowledge accessed and shared means to be able to maintain the network of relationships by regular interaction, management of the relations, joint goals and mutual dependency (Galaskiewicz, 1985) being the basis for network governance (Gulati and Singh, 1998). Network governance mechanisms will be outlined below in more detail.

2.4.3.1 Knowledge sharing enablers and hindrances

Beside their own ability to explore knowledge and share knowledge in networks, companies need to consider some other KS enablers and hindrances. First of all, the knowledge type can be a hindrance or a facilitator to share knowledge depending on company aim and network characteristics. As already outlined above, researchers found that explicit knowledge can be easily transferred between individuals and organisations, but tacit knowledge such as skills, know-how, and contextual knowledge can only be accessed in its application and is slow and expensive (Grant, 1996a; Kogut and Zander, 1992; Nonaka, 1994). In CR tacit knowledge is either transferred by proximity, informal ways such as social relations (Hoffmann et al., 2011) or through an informal KS network with strong rules for participation (Dyer and Nobeoka; 2000; Nonaka, 1994). Strong rules for participation can be rules of interaction that especially develop during long term CR (Clarysse et al., 2014). Informal

KS networks can be based on social relations that help to manage knowledge flows within partnerships (Dyer and Nobeoka, 2000; Nonaka, 1994). That is, to say a two-layer network perspective, as CR can exist at the same time due to formal relationships based on resource exchange, that belong to their value chain (Hinterhuber, 1994).

Summarising the above, CR with informal KS network or well-developed KS routines (Dyer and Nobeoka, 2000) will be able to better share knowledge. KS routines cannot often be found in networks, and if, they are more likely to develop in closed networks (Coleman, 1988; Walker, Shan and Kogut, 1997) than in more open networks (Grant and Baden-Fuller, 2004) due to their deep interaction of network agents. The role of closed and open networks will be further explained below in the section about network structures.

Particularly geographically dispersed networks need good KS mechanisms to ensure effective KS between their partners (Hoffmann et al., 2011). In contrast, clusters are influenced by a great geographical proximity of actors enabling close and direct interaction (Powder and St. John, 1996).

Therefore, proximity as KS mechanism has been researched in the areas of geographical clusters.

Proximity means the closeness of actors to each other (Inkpen and Tsang, 2005) and it can enable KS as actors can maintain a strong frequency of interaction (McEvily and Zaheer, 1999) and the sharing of tacit knowledge (Helmsing, 2001).

Beside proximity, social relations that form informal networks of exchange play an important role for successful KS in CR (McEvily and Zaheer, 1999) as explained at the beginning of this section. Due to the importance of social relations for KS, they are outlined in more detail below. Social ties can reduce organisation and monitoring costs for the effective use of network resources between networking organisations (Dyer and Singh, 1998) and can facilitate the exchange of tacit based knowledge and experience (Hoffmann et al., 2011). Nevertheless, social relations can also raise a certain complexity as they are defined by mutual dependence between interacting parties (Emerson, 1962), as well as possible interpersonal hierarchical subordination (Caimo and Lomi, 2014). Mutual dependence in turn influences reciprocity which is the mutual exchange of resources and not a

one-sided approach to KS (Ahuja and Carley, 1999). Reciprocity is seen as a structural characteristic of social relations that can affect hierarchical structure and hierarchical dependence of individuals (Caimo and Lomi, 2014). The hierarchy in networks is shown by the degree of how reciprocal relationships are in networks (Krackhardt and Hanson, 1993). Less reciprocal relationships can be teamwork; strong reciprocal networks would be more hierarchical than teams (Ahuja and Carley, 1999). Reciprocity can promote trust (Uzzi, 1997) as well as close interaction and the understanding of complex problems (Tortoriello and Krackhardt, 2010). Consequently, reciprocity is an important determinant for KS (Caimo and Lomi, 2014) as it raises the question of equality in relationships (Emerson, 1962).

Summarising the above, even though there is no strong hierarchy present in social relations that form informal networks, reciprocity and mutuality can determine a certain hierarchy and therefore influence the flow of knowledge between individuals within the network. By informal and formal patterns of behaviour they form network relations of different kind (Jones, Hesterly and Borgatti, 1997; Caimo and Lomi, 2014) influencing the structural attributes of network and KS, as outlined in the next section.