Date of Award


Document Type

Doctoral Thesis

Degree Name

Doctor of Philosophy


Management & Enterprise

First Advisor

Dr John Hobbs

Second Advisor

Dr Breda Kenny


National governments and policy makers alike need data and expertise as they seek to develop accurate and relevant cluster policies and initiatives. It is argued that clusters also have life cycles similar to the way industries, products, and technologies have a life cycle, including a variety of stages (Ingstrup and Damgaard, 2013; Jia et al., 2015; Fornahl and Hassink, 2017; Ferrari et al., 2020). This research addresses three objectives: 1. Analyse the longitudinal development of a cluster to record, measure and analyse its evolution over a three-year period; 2. Create a new methodology to support cluster life cycle stage identification; 3. Support policy makers in developing and implementing tailor-made policy initiatives relevant to the cluster’s current stage along its respective cluster life cycle. For the very first time, V-LINC methodology is applied in a longitudinal capacity, to record, visualise, and analyse the BioWin cluster and its ecosystem. A conceptual model, based on three pillars (Economic Impact, Cluster Organisation and V-LINC) encompassing twelve carefully selected variables, is created to identify the stage a cluster is positioned in the cluster life cycle. The outputs of a longitudinal V-LINC analysis measures the effectiveness of cluster policies/initiatives and if they are relevant to the cluster’s identified life cycle stage. This can help to further develop clusters and support its members’ internationalisation. The key findings of the research contribute to the understanding of how clusters at different stages of the cluster life cycle operate and what supports they require. It is also vital to comprehend what policy initiatives are required at each stage of the life cycle, as a ‘one-size-fits-all’ policy implementation does not work. This research has practical implications for policy makers and managers of cluster organisations to name but a few. There are also implications for researchers focused on clusters, cluster life cycles, longitudinal cluster analyses and cluster policy with the empirically tested model of cluster life cycle stage identification contributing to the cluster literature.

Creative Commons License

Creative Commons Attribution-Share Alike 4.0 International License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 International License.

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