Abstract

Many arts organisations can generate large amounts of value through their activities and networks, but often find it difficult to gather, analyse and evidence the data that can inform business decisions and leverage opportunities for product and service innovation. Compared to larger corporations, the creative ecosystem in which they operate depends on “quick business” and requires them to be more agile, adaptive and faster when identifying hidden potential within their networks. Moreover, their interdisciplinary and collaborative ways of working create emerging opportunities for spin-off companies and other entrepreneurial ventures. This study (part of the Arts API Project) aimed to examine the networks of arts organisations to understand some of their defining features and characteristics. The project aimed to show that by visualising and analysing relational data, it was envisioned that arts organisations would be able to operate on a more evidence-based, commercial and entrepreneurial basis, enabling better informed decision making and more defined business strategies. This paper focuses on the role and value of big data in the Arts and Humanities, provides the context and background to the Arts API Project and outlines the methodological approach, presenting one particular aspect of the larger research project. Adopting the technique of Social Network Analysis (SNA), the networks of five UK-based art organisations were visually mapped and analysed using measures such as Density, Connectivity, Centralization and Clique Participation Index. Within the limitations of the study, the findings reveal valuable insights on the effect of de/centralisation of information flow within creative networks, the importance of maintaining a balance between weak and strong network ties and mitigating risk by distributing responsibility across networks.

Full Text
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