Besides network characteristics, other factors influence innovation exchange. This paragraph discusses how different ties affect the development of core and noncore technologies and how they affect innovation exchange. Besides from that, the phenomenon of redundancy and nonredundancy and its effect on innovation exchange is discussed. Finally, Coleman’s social capital theory and Burt’s structural holes theory and their effect on innovation exchange are discussed. Throughout the entire paragraph, a third set of success factors is derived from the theory. The paragraph is structured according to three important network characteristics.
Three important network characteristics that affect the development of core and noncore technologies are the number of direct ties, the number of indirect ties and the nonredundancy in the network (Van Haverbeke et al., 2012).
1. Number of direct ties in the network
2. Number of indirect ties in the network
3. Nonredundancy in the network
A direct tie exists between two individuals when the two individuals know each other directly.
From a competence perspective, direct ties have the advantage opening up and developing new sources of knowledge (Van Haverbeke et al., 2012). For this reason, direct ties speed up innovation developments. Apart from that, direct ties can be used to reflect on the existing knowledge within the company. A third advantage is that investments in and risks of research and development [R&D] can be divided amongst the collaborators. These advantages are stronger for the exchange and development of core technologies than for noncore technology. The reason for this is that, for core technology, it is important to have clear and correct communication. Using direct ties is the best way to make sure that communication happens in the right way. The development of noncore technologies relies more on having access to new information and knowledge. Having direct ties for this purpose therefore is not useful since people who are connected through direct ties, often own similar information and knowledge.
From a governance perspective, direct ties are good because over time they can develop into strong ties and strong ties are good for building trust between people. Another advantage is the control over partners and the limitation of freeridership as partners are less likely to start freeriding while in a strong tie with someone. A disadvantage from a governance point of view is the risk of information spillovers (Van Haverbeke et al., 2012).
Besides the before mentioned advantages, direct ties may develop disadvantages when they are present in too large numbers. Three reasons are mentioned for this counter productivity:
“First, a large alliance portfolio creates a risk of dealing with many unfamiliar streams of knowledge that are increasingly difficult to integrate (Ahuja & Katila, 2001). Second, management attention and integrations costs may grow exponentially beyond a certain number of alliances (Duysters & de Man, 2003), decreasing a firm’s effectiveness in managing its alliance portfolio (Deeds & Hill, 1996). Third, the risk of spillovers or free riders tends to grow with an increasing number of alliance partners.” (Van Haverbeke et al., 2012, p. 786)
This means that with increasingly large networks, the marginal benefits of collaborations decrease whilst the marginal costs increase.
Success factor: Number of direct ties (medium for core technology), Avoidance of freeridership, Avoidance of information spillovers
Influence of strong ties on the exchange of innovations
When exchanging innovations, ties are necessary between the sender and the receiver of the innovation. The question that rises is whether strong or weak ties are more effective in exchanging innovations. Strong ties will be considered first.
Let us first have a look at strong ties:
Consider, now, any two arbitrarily selected individuals -call them A and B- and the set, S = C, D, E, … , of all persons with ties to either or both of them. The hypothesis which enables us to relate dyadic ties to larger structures is: the stronger the tie between A and B, the larger the proportion of individuals in S to whom they will both be tied, that is, connected by a weak or strong tie. This overlap in their friendship circles is predicted to be least when their tie is absent, most when it is strong, and intermediate when it is weak. (Granovetter, 1973, p. 1362)
The stronger the ties are between two persons, the more likely it is that a third person, who is friends with one of the two, will become friends with both. When person A and B are close friends, person C, who is only friends with A, is likely to become friends with B as well. The reason for this is because B and C will spend some time together. If A spends 60% of the time with B and 40% of the time with C, then C, A and B are together 24% of the time (Granovetter, 1973).
Another reason Granovetter (1973) gives for why C and B are likely to become friends is that the stronger the tie between A and B is, the more similar A and B are. If A and C also have a strong tie, they are also similar, which means that C and B are also similar, making it more likely for them to develop a strong tie.
This suggests that when trying to reach new people in exchanging innovations or trying to acquire new information, strong ties are not effective, as its members already know most of the innovations in the strong ties network. This suggests that weak ties might be more effective in exchanging innovations and this suggestion is more or less supported by Granovetter (1973) who mentions the strength of weak ties.
Indirect ties are ties between the focal company and the partners of its partner (Granovetter, 1973). For example, AFI has a direct tie with Recaro, since Recaro builds seats for AFI aircraft. KLM E&M can be connected to Recaro through AFI. In this case, KLM E&M has an indirect tie with Recaro. In contrast to direct ties, which deliver both resources and information, indirect ties primarily provide information (Ahuja, 2000). Indirect partners serve what can be called a “radar” function, since they are on the lookout for new technological developments which they can pass on to the firm (Ahuja, 2000). The main advantage of indirect ties therefore is that they provide new information.
Indirect ties also have disadvantages depending on whether information about core or noncore technologies is exchanged.
Indirect ties are expected to be not so strong in their use for core technologies. This has two main reasons, the first one being that knowledge from a firm can spill through its direct partner to the partner’s partner (Gulati & Gargiulo, 1999). Since the firm only has an indirect tie to the partner’s partner, the firm has little control over the partner’s partner, which can lead to freeridership. The second reason is that the information is rather “noisy”, which means that the information contains gaps and errors (Ahuja, 2000). Since information is passed through the direct partner first, this means that information can be changed and misinterpreted while it is being exchanged. This is a disadvantage since information for core technologies needs to be very specific and fine-grained, meaning that even the smallest details are known.
For noncore technologies, the fact that information is more general and “noisy” is expected to be less important since for noncore technologies it is more relevant to know about the newest technologies rather than knowing exactly how new technologies work. The insight in and overview of new technologies which indirect ties provide, outweighs the risk of spillovers, since the spillover of the general and noisy information is less of an issue than spillover of detailed information.
The research which Van Haverbeke et al. (2012) performed has confirmed what has been described above, however they could not find enough evidence to scientifically proof that indirect ties have a stronger impact on noncore technologies compared to core technologies. Also, they could not proof that the combined effect of direct and indirect ties is stronger for core technologies compared with noncore technologies.
Success factor: Number of indirect ties (noncore technology), Noisiness of information
Influence of weak ties on the exchange of innovations
According to Granovetter (1973): “except under unlikely conditions, no strong tie is a bridge” (p. 1364). Weak ties can serve as a bridge, transporting information between individuals. The strength of weak ties is that whatever is passed through weak ties, reaches a larger number of people and crosses a greater social distance than whatever is passed through strong ties. Also, strong ties are typically concentrated within particular groups while weak ties connect different smaller groups.
Granovetter (1973) also considers differences in race in his research. According to Granovetter: “weaker interracial ties can be seen to be more effective in bridging social distance” (p. 1369). This means that whatever is transferred between two persons, bridges a larger social distance when being transferred through a weak and interracial tie than through a strong tie between persons from the same race.
Indirect contacts are typically reached through ties in the “weak sector” and these ties are: “the channels through which ideas, influences, or information socially distant from ego may reach him” (Granovetter, 1973, pp. 1370–1371). In order to receive these “new” ideas, influence and information, it is therefore important to bridge those weak ties. Crucial information is often received from individuals to whom the receiver has weak ties (Granovetter, 1973).
Direct and indirect ties combined
Direct ties can serve as a bridge between a firm and its indirect ties. Therefore, direct and indirect ties can operate together and according to van Haverbeke et al. (2012) should be considered jointly. As discussed before, the information from indirect ties is less valuable for core technologies. Besides that, an increase in the accumulated number of direct and indirect ties leads to an accumulation of disadvantages. In their research, Van Haverbeke et al. (2012) found that the more direct ties, the smaller the benefit of indirect ties becomes. They did however not find evidence supporting their expectation that this effect is stronger for core technologies relative to noncore technologies.
Influence of weak ties versus strong ties on the exchange of innovations
For the exchange of innovations, this suggests that more innovations can be exchanged through weak ties than through strong ties. Weak ties should therefore be established between employees in companies that have merged. A way of maintaining weak ties is by organizing meetings and conventions. Granovetter (1973) explains that maintaining weak ties is one of the most important reasons for organizing meetings and conventions. Granovetter also mentions that information is more likely to reach the intended receiver when it is earmarked for that specific person. When information is not being transferred through personal ties but through mass media, it is likely that the receiver does not take the information seriously and that no further action will be taken (Rogers, 1962).
Trust is another important factor in transferring information. Thrust in a leader is gained when the people are in some way connected to that leader either directly or indirectly through someone they know. Besides that, leaders have no reason to be trustworthy or responsive to people they do not know (Granovetter, 1973). Therefore, short paths between leaders and potential followers enhance trust in leaders.
An important notion is that whenever too many bridges need to be crossed in order for information to be transported from one person to the other, the information is likely to never arrive at the receiver. The reason for this are the costs of errors which occur in the information (Granovetter, 1973).
Success factor: Emotional intensity, Intimacy, Reciprocal services which characterize the tie
According to Den Hartigh et al. (2009) “strong connections in the core of the network make it possible to increase network effectiveness” (p. 10). However, having only strong connections results in missing out on new technologies whilst being locked in to familiar technologies. This can be imagined since a group of closely related people (strong ties) are often interested in the same things and therefore, by staying in this group, the members are exposed to less new information. You will learn less from a close friend who looks a lot like yourself than from someone who is completely different from you, since this person is likely to bring more new and innovative information to you. The lesson here is to maintain connections to companies or persons who are located in “the periphery of the network” (E den Hartigh et al., 2009, p. 10). This compensates for the weakness of strong ties in the core network by making the network “more varied and more open to new actors” (E den Hartigh et al., 2009, p. 10). and making the network “able to respond more flexibly to market trends” (p. 10).
Success factors: Strong ties in the core network, Weak ties in the periphery
Nonredundant network structure
Van Haverbeke et al. (2012) mention that the amount of pathways where knowledge can flow through is increased by redundancy in networks. Redundancy in networks has effects on the creation of core and noncore technology. Two types of networks can be distinguished when looking at redundancy, which are the redundant and the nonredundant network. It is argued that both for the creation of core as for noncore technology, a nonredundant network structure is better. However, the positive effect of a nonredundant network structure is stronger for the creation of core technology relative to the creation of noncore technology (Van Haverbeke et al., 2012).
Nonredundant networks work better for the creation of core technology (Van Haverbeke et al., 2012). In redundant networks it is easier to steal information and start freeriding. Trust is important, however, when the benefits outweigh breaking the tie, partners are tempted to break the tie and walk away with the knowledge. Also, firms are generally already knowledgeable about their core technologies and are therefore less dependent on external knowledge from partners.
For noncore technology, the value of a nonredundant network is comparatively lower. A nonredundant structure offers access to new information, while at the same time limiting room for knowledge spillovers. Redundant networks however have the possibility for the buildup of shared absorptive capacity and triangulation, which are useful advantages when exploring new fields (Van Haverbeke et al., 2012). Shared absorptive capacity is the ability of firms to see the value of new information, to process it and use it to their own advantage. Triangulation is the method in which multiple sources or perspectives are used to validate something. For example, three companies that work with different methods can test one innovation. This way, companies can be more confident about the test results.
This shows that there are arguments supporting both options. The research by Van Haverbeke et al. shows that both a redundant as a nonredundant network has a positive effect on the development of noncore technology, however no proof has been found to prove which network has a stronger effect.
Success factor: Amount of trust, Protection against theft of information, Amount of shared absorptive capacity, Level of triangulation
Burt (1992b) stresses the importance of nonredundant ties when looking at them from a competence perspective. Nonredundant ties offer access to new and unique information. Redundant ties should be avoided since there are costs associated with maintaining ties. Besides that, only a selected number of ties should be maintained, which are the ties that bridge structural holes
Coleman (1988) has a different view on redundant and nonredundant ties. He mentions that redundant ties may reduce governance risks by building up trust and social control. According to him, it is therefore good to maintain redundant ties in the network. Another reason for maintaining redundant ties is that they increase the network density which is good for social capital, which can exist as reputation, trust, social norms, and social control (Coleman, 1988).
Success factor: Number of nonredundant ties, Number of structural holes, Amount of social control, Costs of maintaining ties
In sociology, two different sociological views exist on how professional networks influence the generation of knowledge. The first view is from Coleman (1988) who mentions how professional networks create solidarity between its members and how these networks make people willing to share tacit knowledge. The second view is from Burt (1992a) and this view is based around information and control benefits. He explains the benefits of having sparse networks with many structural holes. The main benefits of having such a network is that they are useful for obtaining nonredundant information (Adler & Kwon, 2002).
Burt focuses on the structural configuration of relationships by looking at structural holes in a network. Burt’s view on social networks and social capital (Burt, 1992a, 1997) is classified by the network literature as an external view. External view means that Burt focuses on external ties and how these can be used to achieve competitive goals. Sparse networks have little redundant ties, allowing people who are in such networks too become the so-called “broker” in the network. Being a broker means that these people control the flow of information between individuals or groups in the network giving them a competitive advantage. Brokers therefore fill up the gaps between people who are disconnected in the social structure. Burt (1992a) describes these gaps in the social structure as structural holes. Being in a nonredundant network puts a firm in the position to control the flow of resources and information and allows the firm to bridge “structural holes” (Burt, 1992b). The structural configuration of networks plays an important role in Burt’s view, since the configuration determines whether and where structural holes exist. According to Rost (2011), Burt hypothesized two hypothesis:
First, he hypothesized that networks rich in structural holes offered opportunities to broker the flow of information. . . . Second, he predicted that networks rich in structural holes allowed entrepreneurial behavior by controlling the form of projects that bring together people from opposite sides of the hole: A person who adds value by brokering the connection between two others is the third person to benefit. (Rost, 2011, p. 590)
For innovation exchange it is important to realize that “persons with contact networks rich in structural holes move information faster, know the parameters of emerging problems earlier, and tailor solutions to a specific group of individuals” (Rost, 2011, p. 590). Research has shown that structural holes enhance innovation (Uzzi & Spiro, 2005). Sociological studies have shown the benefits of structural holes for the diffusion of information (Rost, 2011). Granovetter (1973) for example found that information travels a larger social distance through weak ties than through strong ties. However, networks with many structural holes also have drawbacks, which are the high maintenance costs of external ties (Perry-Smith, 2006) and their low potential for transferring tacit knowledge (Hansen, 1999).
Coleman’s (1990) sociological view on how professional networks influence the generation of knowledge focuses strongly on the quality of relationships between exchange partners. He expresses the quality of relationships in the strength of their ties. The conclusion that can be drawn from his theory is that social capital investments become more valuable when stronger ties exist between exchange partners (Coleman, 1990)
Coleman (1990) uses so-called “credit slips” to explain his theory. When person A does something for person B, person B is expected to do something in return for person A. In this case, A makes a social capital investment in B, meaning that A invests resources in B. The obligation from B to help A can be called a credit slip that is owned by person A.
Coleman’s focus on the quality of relationships is important since a good relationship between A and B plays a large role in determining the value of the social capital investment. When A and B are connected trough a weak tie there is a larger chance that person B does not (fully) pay back person A, which makes A’s social capital investment worth less. Therefore, exchange partners should invest in establishing strong ties to allow social capital investments to reach their maximum value (Coleman, 1990).
In strong ties, lots of credit slips are being paid back to others. While doing so, lots of time is being spent together. In order to exchange tacit and complex information, spending lots of time together is needed. During the time in which credit slips are paid back, tacit and complex information can therefore be exchanged (Hansen, 1999).
Rost (2011) states that: “weak network architectures have no value without strong ties, whereas strong ties have some value without weak network architectures but are leveraged by this type of structure” (p. 588).
Structural holes theory versus social capital theory
Some researches suggest that both Burt’s as Coleman’s view are correct and that their views complement each other rather than being substitutes. The results of the research done by McFadyen, Semadeni & Cannella (2009) support both Burt’s and Coleman’s view by showing that scientists who combined strong ties with sparse networks published more in high impact journals than other scientists. The success of these scientists could be explained by combining Burt’s and Coleman’s view. The strong ties had led to an advantage due to solidarity and the scientist were better in terms of control and information due to the use of sparse networks.
Coming up with new ideas is an important step in the innovation process. Rost (2011) says the following about the process of coming up with new ideas:
Individuals with networks that include many structural holes (Burt, 1992a) or individuals who occupy a peripheral position in a network (Perry-Smith & Shalley, 2003) have more opportunities to come up with new ideas because they connect people with diverse perspectives, different outlooks, varying interests, and diverse approaches to problems (Ibarra, 1992; Lin, Ensel, & Vaughn, 1981; Lincoln & Miller, 1979). (Rost, 2011, p. 590)
Four types of network structures can be distinguished: research network, development network, diffusion network and production network (FAS.research, 2006). For the exchange of innovations, the diffusion network is relevant. The description of such a network is provided by den Hartigh et al. (2009): “A diffusion network consists of a limited number of hubs, each connected to a large number of periphery actors. There are many structural holes, i.e., there are hardly any relations among the periphery actors” (p.11). To promote innovation exchange we want a diffusion network and therefore its characteristics form success factors for innovation exchange.
Success factors: Large number of periphery actors, Large number of structural holes, Hardly any relations between periphery actors
Three network characteristics affect core and noncore technologies. These are the number of direct ties, the number of indirect ties and the nonredundancy in the network (Van Haverbeke et al., 2012). As concluded by Van Haverbeke et al. (2012):
Direct ties have an inverted U-shaped effect on both core and noncore technology, and the effect is relatively stronger for the former. The results furthermore show that indirect ties play a positive role in noncore technology development and that this effect is not hampered by the number of direct ties a firm has. In contrast, indirect ties seem to hamper core competence development when companies have a lot of direct ties. Finally, firms are found to benefit from nonredundancy in their alliance network in their efforts to strengthen their core technology. (Van Haverbeke et al., 2012, p. 784)
The effect of the above mentioned three characteristics are optimal for core and noncore technologies under quite different network structures. This poses a challenge for companies trying to strengthen their core and noncore technologies at the same time because different network structures apparently lead to different levels of development (Van Haverbeke et al., 2012).
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