Business Clustering in New Zealand: The Creation of Competitiveness in a Regional Cluster and The Influences of Intermediaries on the Cluster Competitiveness
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Business clustering significantly contributes to growth and competitiveness. Studies have examined aspects of clusters related to the creation of competitiveness from different levels of analysis, but less research has been done on the collective contribution of environment, knowledge, and innovation. There has also been a paucity of research to examine how knowledge is created and dispersed through the cluster by the action of intermediaries. This research adds to this literature by combining these theoretical perspectives to examine how competitiveness is created in clusters using a New Zealand example, which also adds to an understanding of how clusters operate in the New Zealand environment. At meso level and micro level, the theoretical foundation is informed by Porter’s Diamond model, the Community Innovation Survey (CIS), and Nonaka’s Spiral model. This research adopts mixed methods design, the embedded mixed-method case study involving a combination of qualitative and quantitative methods. The single case study is on the AgBio cluster in Hamilton, the Waikato region. Data collection is conducted through semi-structured interviews with 18 interviewees representing 19 cluster members and CIS-style survey completed by 13 respondents from 14 companies. The participants to the interviews and survey represent nearly 40 per cent and about 29 per cent of the cluster members respectively. These participants are managers, directors, CEOs, or business owners. Overall, the AgBio cluster is deemed a competitive cluster. Different factors contribute to the cluster competitiveness. First, the cluster strengths include diverse memberships, the presence of leading companies, the attractive amenities of Waikato Innovation Park, the commitment of the Park to promoting networks and collaborations, and the support from the Business Growth team. Second, the cluster members have a positive attitude towards innovation, engaging in product and process innovations, as well as other innovation activities. Third, the cluster benefits from the regional competitiveness. Last, the intermediaries contribute further to the cluster competitiveness, in relation to knowledge creation, transfer, and implementation. This research suggests an adjustment to the Diamond model that is less applicable for assessing competitiveness of small regions with limit local determinants. Furthermore, the effort to promote a diverse cluster may limit opportunities and areas for intra-cluster interactions and collaborations, particularly in small clusters.