An exploration of the process and nature of innovation in clusters

Abstract

Interest in the subject of clusters has been steadily increasing over the last few decades. One reason for this is that organisations in the cluster often out perform organisations from the same industry located outside of the cluster. One of the predominant explanations for the clusters ability to achieve this is through innovation. The cluster literature shows that clusters are a important source of innovation, and that innovation plays a key role in maintaining the competitiveness and existence of the cluster. However, although innovation is discussed in the literature, it can be thought of as a black box or fuzzy concept (Markusen, l999b). This is because although the drivers to innovation are stated, and innovation is known to be a positive outcome for the cluster, innovation is not studied as a concept, and statements concerning innovation are often made without evidence or justification. Therefore relatively little is known about the process or nature of innovation as it occurs in clusters. The research question was devised from this position, and aimed to investigate what was actually meant and understood by innovation in clusters. To this end the research question was: What is the process and nature of innovation in clusters?â I this thesis I report on empirical studies undertaken in two clusters, in which I used semi- Structured interviews. Aer a analytical review of the interview findings I discuss the results from a cross case comparison; this is complemented with data from the extant literature. The results from the comparison are used to generate a empirically derived model of the process of innovation, and a definition of the nature of innovation in clusters. The model explains that the process of innovation progresses through five steps: Ignite; Gather; Spark off; Create and Diffuse. The definition of the nature of innovation is understood via five essential characteristics; that innovation is major, undertaken continuously, is time compressed, problem solving, and survival driven. I combination the model and definition leads to a analytically generalisable view of the process and nature of innovation, which can be applied to clusters as a whole.