This chapter aims to answer the first sub-question by using existing literature. The first sub-question was formulated as follows:
Sub-question 1: Which factors contribute to successful exchange of innovations between companies?
Lots of research has been done in the field of innovation exchange. This research can be used to create a list of success factors. Different literature streams focus on different parts of the innovation exchange process. The literature streams that are used in this research are the literature stream on inter-organizational relationships, alliances governance literature, standards battles literature and social network literature. The literature stream on inter-organizational relationships focuses on relationships between firms and how these affect the exchange of innovations. The alliance governance literature focuses on how the governance of alliances affects the exchange of innovations and the standards battles literature describes motives for collaboration between firms and its relation to innovation exchange. The three different perspectives of these three literature streams are used to describe why firms collaborate and exchange innovations (2.1). The social network literature, which focuses on how different network structures affect the exchange of innovations, is added to describe how social networks affect innovation exchange (2.2). After that, a review of how different characteristics and designs of networks affect innovation exchange is provided (2.3). The final paragraph provides the reader with an overview of all the success factors that were found in the existing literature (2.4).
2.1. The effect of collaboration on innovation exchange
The effect of collaboration on innovation exchange can be discussed from three different perspectives that are: the inter-organizational relationships perspective, the standards battles perspective and the alliance governance perspective.
Inter-organizational relationships perspective
Lots of studies have shown the positive effects of inter firm networks on innovation and the development of new technology (De Man & Duysters, 2005). Alliances and inter firm networks allow knowledge and existing innovations to be transferred between partners. The competitive advantage gained from collaboration between firms is that these firms get access to new information and knowledge. Besides that, they can combine their knowledge in order to create innovations and they can gain access to new product markets (Hagedoorn, 1993).
According to Nooteboom (1998), three types of inter-organizational relationships exist: vertical, horizontal and diagonal relationships, which are respectively between buyers and suppliers, between competitors and between firms that operate in different markets. Before the merger, AFI and KLM E&M were in a horizontal relationship as they were competitors. At this point, after the merger, they still have a horizontal relationship as they operate independently of one another.
The inter-organizational relationships literature has two different perspectives on knowledge flows in collaborations (Van Haverbeke et al., 2012). A positive role for knowledge flows between firms is assumed through the competence perspective that assumes that knowledge flows can lead to the creation of new knowledge and technologies. The negative perspective is the governance perspective that assumes that knowledge flows between firms are undesirable spillovers of knowledge. These spillovers are negative in the sense that they can lead to opportunism and freeridership. Opportunism and freeridership mean that people or companies who can catch the overflow of knowledge “steal” the knowledge and for example establish their own company to compete against the company from who they stole it.
Standards battles perspective
An important factor which influences the diffusion, and therefore the exchange, of innovations, is whether the innovation is accepted as the new standard (van de Kaa, 2013). Imagine one department that has developed a new tool that has proven to be better than any other tool currently being used. An important factor that determines whether others in the company want to use this new tool is acceptance of the tool. The company can benefit when everyone uses this improved tool i.e. accepts the new standard. Having one standard means that the company can benefits from economies of scale. In the case of the tool this means that the tool, and usage of the tool, becomes cheaper when more people use it. However, companies need to be careful when selecting a new standard. Choosing the right technological standard can mean the difference between winning or losing in the market (E den Hartigh et al., 2009). When several standards compete for becoming the preferable and most widely used standard this can be called a standards battle.
The relationship between standards battles and innovation exchange can be found in the diffusion of innovations (Rogers, 1962). New innovations will be exchanged whenever they are the (potential) new standard. Each time someone wants to exchange an innovation, a small standards battle occurs in which the recipients of the innovation have to determine if the innovation should replace the old standard. Therefore success factors for innovation exchange are related to the factors that determine which standard will win the standards battle, since innovations are more likely to be exchanged and accepted when they exhibit the potential to become the new standard.
An important motive for companies to exchange innovations is in order to establish a standard, at least within the companies, but preferably also within the industry (van de Kaa, 2009). The theory on standards battles discusses amongst other things, factors that affect which standard will win the battle (van de Kaa, Van den Ende, De Vries, & Van Heck, 2011). In recent years these standards battles have lasted increasingly shorter (van de Kaa et al., 2011), which means that being able to predict or influence which technology will become the next standard has become more important (E den Hartigh et al., 2009; van de Kaa, 2009).
In the aircraft maintenance industry, a standards battle could be between performing aircraft maintenance inside a hangar or outside on the arrival and departure platforms. Each have their advantages and disadvantages, but as soon as one standard wins the standard battle, all technology surrounding aircraft maintenance is designed around this standard. In the example, it is clear that over the past years, all technologies were designed around working on aircraft inside hangars. Over the last years however, more and more new technological developments are being developed around working in the open air, so there seems to be a shift in the standard and the standards war might be reopened.
Two reasons for collaboration can be distinguished when looking at technology standards battles. The first one is that it is nearly impossible for one company to create a new standard by itself (E den Hartigh et al., 2009). Setting a standard requires lots of resources and capabilities and one company usually simply does not have enough of these resources and capabilities. For this reason, collaboration with other companies is required. This can for example be trough cooperation’s, alliances or as in the case of AFI KLM E&M through a merger. The second reason is that the outcome of standards battles is inherently uncertain (E den Hartigh et al., 2009). This uncertainty is increased by so called network effects. Network effects are the phenomena that whenever the number of users increases, the financial benefits of using that technology increases as well (Katz & Shapiro, 1985). The number of users can be referred to as network size, which is determined by: “the number of suppliers and users of products based on a common technological standard” (E den Hartigh et al., 2009, p. 7). This uncertainty also increases when a too large number of different technologies are available to the market. This increases the uncertainty for actors in the market, which eventually will decrease innovation efforts by these actors. This uncertainty can be limited by standardization, which offers some certainty depending on the degree of flexibility of the standard (van den Ende, van de Kaa, den Uijl, & de Vries, 2012). More flexibility in the standard gives more room for innovation while less flexibility increases the certainty for the actors investing in the standard (Erik den Hartigh, Ortt, van de Kaa, & Stolwijk, 2016).
In short, it is important for companies to strive towards a technological standard. By collaborating with other companies, which amongst others means exchanging innovations, companies can influence which technology will become the next standard. Besides that, exchanging innovations can lead to working together on developing new technologies together, in which it is more likely that the new technology will become the next standard when a larger part of the network is included in its development (van de Kaa, 2009).
Alliance governance perspective
Alliance governance talks about different ways of designing alliances (Kogut, 1988). According to Jiang (2009), sharing knowledge between the companies in an alliance leads to more innovation. They have compared different types of alliances and their effect on the performance of firms. The results of their research show that the closer the cooperation between companies, the more innovative both companies are. Their results further show that knowledge sharing, knowledge creation and the interaction between both, contribute to how both companies perform in terms of innovation.
For KLM E&M, even if they are not an alliance but a merger, this might imply that the merger with AirFrance Industries can potentially boost its innovative performance. The first success factors that can be derived from the alliance governance perspective are stated below.
Success factor: Closeness of collaboration, Amount of knowledge sharing, Amount of knowledge creation
Companies can have different motives to cooperate (Tidd & Bessant, 2009). Two main types of motives can be distinguished that are: strategic and tactical motives.
When a company has strategic motives, this means that the company wants to gain market share and/or wants to acquire knowledge from its partner. An example of such a motive is a market motive, which can be airlines that form an alliance and herewith expand their network by adding more destinations to their existing network. This way they can gain access to new markets.
When a company has tactical motives for cooperation, they are interested in reducing factors such as time, costs and risks by sharing these with a partner. An example of such a motive is a technological motive, for example when a car developer cooperates with a radio developer. This way the car developer can share the investment costs of developing a new radio for its new cars.
Tidd and Bessant (2009) stress the importance of having an explicit policy when companies want to learn from their partner. Other motives from cooperation are technological motives, market motives and organizational motives. Technological motives are based around sharing investments in the development of innovations
Success factor: Existence of an explicit innovation sharing policy
Another distinction that is made is the distinction between core and noncore technologies. This distinction is important when looking at how different relationships affect the development of new technologies when firms share knowledge about innovations.
The development of core technology has to do with the firms core business, which is the business that is currently most relevant for the firm. The development of a firm’s core technology has short-term benefits as it affects the technology currently being used in the firm. The information making up the core business is therefore crucial for the firms’ competitive advantage on the short-term. In order to maintain this competitive advantage, it is crucial to keep this information away from competitors. Therefore, firms focus relatively more on reducing the risks of collaboration than on profiting from the possible benefits of collaboration (Cassiman & Veugelers, 2002).
The development of noncore technology is different in the respect that this technology does not yet count as a competitive advantage for the firm. The amount of information already gathered about the new technologies is usually still quite small. The risk of information leakage is outweighed by the value of new information and the use of other firms their resources. Therefore, firms tend to value the benefits of collaboration over its risks (Gilsing & Nooteboom, 2006).
In conclusion, whether firms focus more on reducing risks of collaboration or on benefits of collaboration is determined by what kind of technology they want to share with their partner. The focus of a firm on competence- and governance-based risks and benefits is related to whether they focus on the development of core or noncore technology. Collaborations established for developing core technologies, focus more on reducing the governance-based risks than on increasing the competence-based benefits. For collaborations established for developing noncore technologies, this focus is turned around i.e. they focus more on competence-based benefits than on governance-based risks (Van Haverbeke et al., 2012).
Many companies want to become more innovative and want to use innovations to stay ahead of their competitors. For companies that are in an alliance it is important to check first in what stage they are. The company can go through different stages and in order to continue with a stage, the previous stage needs to be implemented first. Tidd and Bessant (2009) identified four stages in the development of an innovative company that is in an alliance:
1. Innovation within each company
2. Exchange innovations between the companies in the alliance
3. Combined effort on developing new innovations
4. Set up a network with external companies and knowledge institutes
This distinction is useful for showing where this research is about, which is the second stage. In reality however, it was found that for example AFI KLM E&M is trying to do all four stages at the same time.
Innovation is known to cost resources, such as time and money, while the result is usually unknown and success is uncertain. Being able to copy successful innovations from another company in the alliance can therefore save resources. Being a commercial company, KLM E&M is required to invest in innovations by itself and therefore being able to copy ideas from AFI can be an advantage which the AFI KLM alliance has over other MRO’s. In order to do so, they need to establish a network in which innovations can be exchanged. Social networks and their effect on innovation exchange will be discussed in the next paragraph.
2.2. The effect of social networks on innovation exchange
A social network is a network of nodes that are connected through ties. Nodes can range from actors to companies and ties can range from weak to strong ties. Ties can be seen as a connection between two nodes. This connection only exists when more or less regular communication exists between the two nodes (Wasserman & Faust, 1994). For innovation exchange to occur, it is essential to create an effective network between people from both organizations. By going through the different characteristics of networks and how these influence the performance of the network, it is possible to find success factors for an effective network and herewith for successful innovation exchange.
The social network literature describes aspects of networks and how these influence the performance of actors in the network (Burt, 2000). Important aspects of networks that can be distinguished are:
1. Strength of the relationships in the network
2. Network diversity or content
3. Network constraint
4. Network size
5. Network density or structure
6. Network hierarchy
Success factor: Density of the network, Network structure, The strength of the relationships in the network, Network diversity, Network content, Network constraint, Network size, Network hierarchy
Since each of these network characteristics affects the performance of the network and herewith its performance in terms of innovation exchange, each of the six characteristics are discussed below and success factors for innovation exchange are derived from them.
Strength of relationships
The strength of a relationship is determined by factors such as emotional closeness, frequency and duration of the relation (Marsden & Campbell, 1984). Another factor which determines the strength of a relationship is the amount of new information that is being exchanged between partners (Granovetter, 1973). These factors determine the strength of the relationship and herewith the ability to exchange innovations, the factors will therefore be used as success factors for exchanging innovations between companies.
Success factor: Emotional closeness, Frequency of the relation, Duration of the relation, Amount of novel information that is communicated
Granovetter (1973) distinguishes between direct and indirect ties. Direct ties reflect relational embeddedness while indirect ties reflect structural embeddedness. Van Haverbeke et al. (2012) explain the difference as follows: “Whereas relational embeddedness refers to information from partners with whom firms have a direct relationship, structural embeddedness refers to information from partners’ partners and beyond” (p. 785).
Ties between different people differ in strength. It can be imagined that the tie between close friends is stronger than the tie between two acquaintances. Granovetter (1973) gives the following definition of the strength of a tie: “the strength of a tie is a (probably linear) combination of the amount of time, the emotional intensity, the intimacy and the reciprocal services which characterize the tie” (p. 1361). With this definition, the strength of ties can be measured and a distinction can be made between strong and weak ties.
Network diversity or content
Network diversity or content describes the essence of relationships. Is the relationship based on friendship or is it purely a business relationship? These kinds of questions describe the network diversity or content.
Diversity in networks may have positive as well as negative influences on the firm performance.
The positives are that firms in a diverse network have access to more diverse information (Nooteboom & Gilsing, 2005) and that firms can match complementary technological capabilities (Hagedoorn, 1993).
The negative aspects are that the diversity can lead to a decreased mutual understanding (Nooteboom, Van Haverbeke, Duysters, Gilsing, & van den Oord, 2007), unfamiliarity between actors in the network and a lack of trust (Goerzen & Beamish, 2005).
Success factor: Access to diverse information, Matching of complementary technological capabilities, Mutual understanding, Familiarity between actors in the network, Trust
Jaffe (1986) explains that when knowledge spillovers exist, the knowledge created by one firm can be taken over by a different firm for a low price. Schilling & Phelps (2007) also explain that: “prior research has shown that spillovers tend to be spatially bounded: Their effect is more pronounced for firms conducting research in similar technological domains (Jaffe, 1986) and geographic locations (Feldman, 1999)” (p. 1124).
Success factor: Level of similarity in technological domains, Level of similarity in geographic locations
Network constraint is defined as the extent to which a person’s network is concentrated in redundant contact (Burt 1992, Chap. 2). Constraint is high in dense networks in which people are directly connected and low in hierarchical networks in which they are indirectly connected (Burt, 2000). Constraint is determined by three other network characteristics: network size, density and hierarchy.
The effect of constraint on the performance of a network can be viewed from two perspectives. The structural holes perspective and the network closure perspective (Burt, 2000). A structural hole is a gap between two individuals who have complementary sources to information (Burt, 1992a). Network closure describes how closely connected actors in a network are. For example, density is one way of describing network closure.
The structural holes perspective believes that performance increases when more structural holes are bridged. The more constrained a network is, the less structural holes are bridged, so the performance of network decreases when constraint increases.
The network closure perspective believes that performance increases with increasing closure of the network. Since more constrained networks have more network closure, more constraint networks have better performance according to this perspective.
Network is size is determined by the number of contacts in a network. Generally speaking, it is believed that more contact lead to more information being exchanged. Network constraint decreases with increasing network size since managers will have to distribute their attention across more contacts. Both from a structural holes as from a network closure perspective, it is believed that performance of the network increases with increasing network size (Burt, 2000).
Technology network effects mean that whenever a company’s network grows, the financial benefit of new technologies becomes larger too. For this reason, network size is an important success factor when exchanging innovations. Exchanging innovations can enlarge the company’s network, which means that the benefits from the innovations that are being exchanged will also increase. Network size is influences by the number of sponsors of a technology and the number of sponsors of a technology is influenced by the diffusion of innovations. More success factors can be found when looking at the further division of technology network effects into direct and indirect technology network effects. “The direct technology network refers to the number of sponsors and licensees of a specific technology. The indirect technology network effect refers to the number of companies that provide capabilities that are complementary to the core technology” (E den Hartigh et al., 2009, p. 8).
Success factors: Network size, Number of sponsors of a technology, Number of licensees of a specific technology, Number of companies that provide capabilities that are complementary to the core technology
Network density or structure
Network density can be defined by the number of observed ties in a network, divided by the ratio of possible ties (Barnes, 1969) or as the average strength of connection between contacts (Burt, 2000). Density is often associated with network closure. In a close network, it is easier to control the behavior of individuals. Burt (2000) states that: “If network closure is the source of social capital, performance should have a positive association with network density” (p. 374). Drawbacks of a dense network are that people in the network are likely to know the same information, resulting in a lack of new information. Besides that, connections cannot broker information between contacts since all members are directly connected to each other.
Schilling and Phelps (2007) have examined the influence of the structure of industry-level alliance networks on firm innovation. They argue that: “two key structural properties of large- scale networks, clustering and reach, play important roles in network diffusion and search” (p. 1123). The role which clustering and reach play and how they influence the transmission of information and its quantity and diversity is also explained by Schilling and Phelps (2007):
Clustering enables even a globally sparse network to achieve high information transmission capacity through locally dense pockets of closely connected firms. Reach increases the quantity and diversity of information available to firms in the network by bringing the information resources of more firms within relatively close range. (p. 1123-1124)
Success factor: Level of clustering in the network, Amount of reach in the network
Schilling and Phelps conclude by arguing that: “networks that have both the high information transmission capacity enabled by clustering, and the high quantity and diversity of information provided by reach, should facilitate greater innovation by firms that are members of the network” (Schilling & Phelps, 2007, p. 1124). They concluded by saying that: “networks that have both the high information transmission capacity enabled by clustering, and the high quantity and diversity of information provided by reach, should facilitate greater innovation by firms that are members of the network” (Schilling & Phelps, 2007, pp. 1123–1124).
Network hierarchy is “the extent to which the redundancy can be traced to a single contact in the network” (Burt, 2000, p. 375). In a hierarchy network, a few contacts are believed to be the source of closure for the entire network. An example is a company in which the network is built around one boss. The two different perspective: the structural holes perspective and the network closure perspective, have contrasting views on how network hierarchy influences a networks performance. The structural holes perspective argues that hierarchy has a negative influence on the performance while the network closure perspective argues that more hierarchy improves the network performance.
The networks characteristics and the success factors that were derived from them were derived mostly from the social network literature. When looking at for example the standard battles literature, success factors can be found that are similar to those described above.
It was for example concluded in the first paragraph that the outcome of standard battles is very uncertain, but it can be influenced when large enough groups with enough influence adopt the new technology. This is the reason why companies make coalitions, because they understand that the outcome of standard battles is determined between different coalitions of companies that have adopted competing technologies (Erik Den Hartigh & Langerak, 2001).
Den Hartigh et al (2009) then concluded that these coalitions have three important characteristics: “the composition of the network, i.e., the numbers of actors involved and the variety of types of actors and the structure of the network, i.e., the interrelations between the actors” (p. 9).
Success factors: Composition of the network, Variety of types of actors, Structure of the network
Besides that, Den Hartigh et al (2009) showed for three network characteristics how they can be assessed: network size, network diversity and network structure. Network size is assessed by “the number of actors” in the network (E den Hartigh et al., 2009, p. 11). The network diversity is assessed by the “types of actors in the network” and the “diversity of types of actors involved” (E den Hartigh et al., 2009, p. 11). The network structure is assessed by its “density”, the amount of “structural holes” and the “type of structure” (E den Hartigh et al., 2009, p. 11)
Success factors: The number of actors in the network, Types of actors in the network, Diversity of types of actors involved, Density of the network, Amount of structural holes, Type of network structure
This shows the similarity in success factors that can be found when looking at how social networks influence the exchange of innovations. It is therefore concluded that lots of useful success factors were derived from the social network literature and that other literature streams show similar success factors.
The next paragraph talks about how different types of ties, nonredundancy in networks and structural holes influence the exchange of innovations. In this paragraph, the third set of success factors for innovation exchange is derived.
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