Innovation Clusters
There is evidence that the creation and growth of new, technology-based enterprises occurs most effectively in geographically-limited clusters.
A cluster, as defined by Michael Porter of the Harvard Business School, is a geographic concentration of competing and cooperating companies, suppliers, service providers, and associated institutions.
The most famous innovation cluster, of course, is Silicon Valley. In such clusters, there is a frequent and strong interaction between many individuals and organisations, on both formal and informal levels. Science parks are an attempt to create clusters of like-minded individuals and organisations and to provide them with their basic infrastructure needs.
However, there is insufficient evidence to suggest that this artificial building of clusters is truly effective. The real clusters like Silicon Valley grew up over significant periods of time and evolved into the structures they now are.
It is difficult to identify the precise building blocks necessary for an effective cluster but certainly many seem to bring together people and institutions involved in business development, finance (and especially venture capital), management, consulting, and research. Many clusters are built around or near a University campus since this provides both research input and a source of new talent.
Clusters seem to have grown in particular parts of the world. This is often due to location-specific factors such as a history of clustering based around an available raw material, or an available transport infrastructure. Other parts of the world seem unable to establish effective clusters. For example, there are few in Latin America though there are areas with potential. There may be cultural barriers present here or there may be maturity issues, with the potential being realised as the area grows into being a cluster.
Some suggest that in a networked world, the value of clustering is diminished; that physical co-location is less important. This seems to underplay the importance of the informal networking that goes on in clustered regions.
Though it may be possible to simulate on the Web or via other technological processes a number of the processes involved in clustering, it is unlikely that all such processes, which are only partially understood, can yet be simulated or re-created.
Clustering is often now seen as a key means of driving regional development. This involves building mutually beneficial private and public sector partnerships through government and regional investment in innovation incubators, science parks and cities, technology transfer offices, etc. Those regions around the world which by accident or design have achieved a clustering effect seem to be better able to achieve and sustain significant success in the global marketplace. Such regional agencies need to identify and understand the real success factors in building and maintaining an effective cluster. There is considerable research going on to identify such factors, but as yet, the jury is still out.
See also the UK Government White Paper Our Competitive Future: Building the Knowledge Driven Economy which states that:
Business development is often strongest when businesses cluster together, creating a critical mass of growth, collaboration, competition and opportunities for investment. Venture capital and business advisers are attracted to the area. Local education and training institutions can help create a pool of skilled labour to meet the cluster’s needs.
January 2000
See also:
Regional Innovation Potential: The Case of the Us Machine Tool Industry
Steven R. Nivin
Ashgate £37.50
ISBN: 0 7546 1008 X
The concept of ‘clustering’ suggests that regional development and innovation potential can be closely linked. Steven Nivin analyses this linkage by looking specifically at the contribution to economic development of technological change. He looks at the processes driving innovation and helps us understand the development of economies. Specifically, the study explores the concept of innovation potential and the factors that result in variations in innovation potential across metropolitan areas, using the US machine tool industry as a case study. To provide a comparison, the same models are also estimated for the semiconductor industry.
The findings indicate that urbanisation economies, localisation economies, human capital, universities, and invention-derived knowledge are significant factors. The study assesses the contributions of three different skill levels of human capital: college educated, graduate degree, and locally produced PhDs in mechanical and electrical engineering. Only the graduate and PhD measures are found to be significant, indicating the importance of having a highly skilled pool of labour within the region.
The influences of the factors appear to be similar across industries with some slight differences.
The transfer of knowledge through patents is also studied. It is found that the transmission of this knowledge is slower between different industries, relative to the transmission within the same industry. This is a useful reminder of the importance of regional development and is a significant contribution to developing economic geography, and public policy.
July 2000