Adaptation and Change in Creative Clusters: Findings from Vienna's New Media Sector

Abstract

This paper investigates some of the features of technological heterogeneity in the New Media cluster in Vienna and the local and global factors that have shaped territorial learning conditions over time. Technological heterogeneity is given a central role in cluster evolution for the expansion of local capacities and opportunities for change. In this paper, it is argued that technological heterogeneity is an important but insufficient motor for cluster evolution. Rather, what is required are local technological capabilities and learning conditions for the exploitation of technologies for operations and procedures that are relevant for firm and cluster performance, as posited by evolutionary theories of technical change. These perspectives are used to interpret the complex, variegated and partially unpredictable features of technological heterogeneity in the New Media cluster in Vienna, revealing the importance of the capabilities embodied in people and local conditions of managing uncertainty mediated via heterogeneity in products, processes and client needs. For this sector, conditions of technological instability create increasing importance for local learning and networks if clusters are to be propelled more deeply into existent or more radically into novel specializations.

Acknowledgements

We would like to thank three anonymous referees for their valuable comments on an earlier version of this article. We gratefully acknowledge the support of our project partners from the University of Kiel, Germany, the University of Hamburg, Germany, University of Bremen, Germany, Lund University, Sweden, University of Agder, Norway, Vienna University of Economics and Business, Austria, Charles University in Prague, Czech Republic, Silesian University in Opava, Czech Republic, University of Ostrava, Czech Republic, University of Neuchatel, Switzerland, and the INSEAD Policy Initiative, Abu Dhabi.

Notes

1. For a more detailed review, see Sinozic et al. (2013).

Additional information

Funding

This work was supported by the European Science Foundation European “Cluster Life Cycles Project” and by the Austrian Science Fund (FWF) [Grant number I 582-G11], and coordinated by Professor Robert Hassink, University of Kiel.