Análisis de datos

The activities for value creation take place at this network level even though the processes governing that value creation may take place elsewhere. This level of network is driven by human actors, who are characterised by diverse knowledge resources and roles that contribute to the overall functioning of the network. For instance, the formal coordination has assigned categorical roles that define everyone’s anticipated contribution. However, the diversity and access to knowledge-based resources are impacted by the extent to which the individual actors are impacted by human agency, absorptive capacity, and the overall knowledge of capabilities within the network that facilitates the collaboration within the overall network. A multitude of social structures define how knowledge acquisition opportunities are either enabled or constrained, and the extent to which value is created.

Figure 15 – Influences on the Science Network

Knowledge and resource flows occur through a variety of subunits. The subunits are characterised by a variety of knowledge content roles and behavioural components. Most of the network activity has been observed within a network composed of actors from the physics,

165 chemistry and biology departments within Durham University and the technology managers within P&G. While the board was developed to insulate the institutional and external network activities, there were still evidence of significant pressures and surmounting expectations as more became external members became involved. Additionally, this network needed to address a communication and joint problem-solving forum where knowledge diversity and the process of innovation could emerge.

There has always been an interrelationship of the natural science disciplines, as each of these disciplines performs a specific role relating to the others. Chemistry is focused on understanding the chemical composition of our world and is often referred to as the central science due to its capability of connecting disparate fields within the physical sciences (Kunn, 1962). As such, a general definition of Chemistry is a study of particles and the chemical bonds. The laws of physics aid chemists in determining the underlying forces that govern movement of the particles under observation. Therefore, Physics is generally defined as the study of properties and movement of matter and energy, which can be associated with anything that moves. There is a long-standing relationship between the cross integration of the studies of physics and chemistry. Biological studies, which are frequently called life sciences, cannot be reduced to chemistry due to theories of evolution and a level of unpredictability of molecular and cellular behaviour. The biological inter-relationship occurs using the laws of physics to understand movement, and certain chemistry based methodological approaches which are employed to understand the composition of cells. This basis aids the communication platform for the shared language requirement of deriving innovation. Academic language from diverse disciplines has the potential to limit communication in this context, as specialized terminology can limit the extent to which ‘outsiders’ can internalise.

A significant and understated benefit of the industrial context and the development of technology at the university lies within the ability to connect inter-disciplinary approaches within the remit of a single project scope and fosters deeper integration into the multi-discipline approach to solving scientific challenges. This unique configuration allowed a platform to inter-relate academic departments extends beyond the traditional departmental format of many university structures. For instance, technical challenges that focused on personal care could integrate project scopes across biology, chemistry, physic, and mathematics. This fosters the potential for novelty to emerge as it not only features a level of knowledge redundancy to allow for absorption but also exposure to diversity in new knowledge acquisition.

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5.6 Chapter Discussion

This chapter of the thesis reviews the various ways in which a university-business network can be analyzed and the impact that various network structures have on the management and coordination of the innovation process. It aims to define methodological insight to the streams in which a university-business network might be studied through illustrating the variations between the macro-level and micro-level views. The variations between these view presents conceptual issues in the analysis as it makes it difficult to identify the boundaries of the network and all the potential resources that may become available, especially in the instance of an open system (Laumann et al., 1983; Wasserman & Faust, 1994).

The micro-level approaches to analysis limit the boundaries to individual level and the types of relations embedded within (Kilduff & Tsai, 2003). The process of innovation and sharing knowledge occurs within the micro-level. However, the university-business relational exchange can be impacted by several significant and powerful external forces and, as evidenced in Chapter 4, the management and coordination of those external institutions plays a significant role on the internal behavior, opportunity identification, and internal management.

As evidenced in the university-business section of the literature review (2.3.3), there are significant efforts and pressures from various external institution on this form of relationship within the United Kingdom. Recessionary pressures and evidence of strained public resources has influenced a greater call from Government for greater university-business engagement across the nation and for shared resources in the pursuit of technology development. The Government hopes to influence the innovation landscape for higher levels production and to stimulate growth economy by better utilize national resources (Salter & Martin, 2001; Metcalfe, 2010; BIS, 2012; Wilson Review, 2012). This is often done in the format of engaging MNCs, SMEs, Universities, Research Institutes, etc which may present opportunities for diversity and heterogeneous knowledge within the network (Knott, 2003) through providing access to weak ties (Granovetter, 1973; Burt, 1992).

However, as the universities connect and their network increases in complexity, a potential for network overload emerges (Marriotti & Delbridge, 2012) and may undermine the ability to develop the integration and relational linkages that are necessary for the complex knowledge transfer (Uzzi, 1996, 1997) associated with innovation development as the value of the knowledge acquisition is largely dependent on the composition of the knowledge shared (Polyani, 1966) in the micro-level network. The resources necessary to ensure that all links are managed appropriately relies on the ability to effectively coordinate multiple levels of network simultaneously.

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CHAPTER 6 SOCIAL STRUCTURES, CONTENT, AND BEHAVIOUR IN