Assessing overall network structure in regional innovation policies: a case study of cluster policy in the West Midlands in the UK

Revisiting the theoretical roots of the key concepts of “embeddedness” and “networks” that underpin many recent regional innovation polices, this paper strives to achieve a more systematic understanding of the overall network structure of geographic agglomerations, which helps to form a more convincing model of regional development based on learning. This also helps to establish an analytical framework with indicators to assess the overall network structure in regional innovation policies. Employing the framework, the examination of cluster policy in the West Midlands highlights its weakness in addressing the overall cluster network structure and the contingent factors influencing the structure. The analysis suggests that there may be similar weaknesses in other regional innovation policies and the theories underpinning them as they share a common weakness in addressing the structural characteristics of overall networks

The Clustering of Organizational Innovation: Developing Governance Models for Vertical Integration

This case explores a cluster of firms that emerged sharing a particular ownership structure. Typically, clusters are thought of as interrelated firms that produce similar products and services. However, we document the emergence and evolution of a cluster of entrepreneurial ventures that developed using a unique governance structure. We explore the deviant case of Renville, MN because of its notable success in developing a series of entrepreneurial ventures that provided producers with the opportunity to vertically integrate.collective entrepreneurship, organizational innovation, joint vertical innovation, cluster, Agribusiness, Research and Development/Tech Change/Emerging Technologies, Q10, Q13, Q16,

Innovation, Learning and Cluster Dynamics

This chapter offers a theory and an analytical framework for the analysis of cluster dynamics, i.e. the innovative performance and evolution of clusters.It develops three types of embedding: institutional embedding, structural embedding (network structure), and relational embedding (type and strength of ties).The analysis is conducted from a perspective of both competence (learning) arising from relations and governance of relational risk, which includes risk of lock-in and risk of spillover.A basic proposition is that innovative clusters face the challenge of combining exploration and exploitation.Hypotheses are specified concerning differences between networks for exploration and exploitation, and concerning combinations and transitions between them.Arguments are presented that in some important respects go against the thesis of the strength of weak ties .Some empirical evidence is presented from recent studies.innovation;organizational learning;clusters;industrial districts;networks

Innovation Clusters: Combining Physical and Virtual Links

Innovation is increasingly seen as a collective action which involves many different actors operating in a cluster context. These clusters are usually conceived as local agglomerations. In this paper it will be argued that they are an important tool to study innovation, but the globalisation of companies and markets and the specific requirements of innovation processes require the expansion of cluster concepts towards virtual dimensions. It will be shown that the combination of local and virtual cluster links improves access to essential resources in innovation. An examples taken from the automotive component sector will illustrate the concept.Innovation, cluster dynamics, automotive components.

Innovation as a latent variable: an alternative measurement approach

In searching for improvements in the measurement of innovation, in this paper we suggest the idea of conceiving innovation as a latent variable or concept, i.e., one that cannot be accurately defined or directly measured. We propose the use of multivariate statistical analysis (a combination of cluster and discriminant analysis) as a possible way to develop indirect measures of innovation that are more appropriate to the intrinsically imprecise nature of the concept to be measured. In this way, the problem of using an ambiguous and subjective ‘innovation definition’ is limited, reducing measurement errors. We obtain an ‘innovation intensity index,’ which is a weighted average of ten different predictors.Measurement; Innovation; Multivariate; Discriminant analysis; Cluster analysis; Latent variable, innovation index.

Cluster Performance reconsidered: Structure, Linkages and Paths in the German Biotechnology Industry, 1996-2003

This paper addresses the evolution of biotechnology clusters in Germany between 1996 and 2003, paying particular attention to their respective composition in terms of venture capital, basic science institutions and biotechnology firms. Drawing upon the significance of co-location of "money and ideas", the literature stressing the importance of a cluster's openness and external linkages, and the path dependency debate, the paper aims to analyse how certain cluster characteristics correspond with its overall performance. After identifying different cluster types, we investigate their internal and external interconnectivity in comparative manner and draw on changes in cluster composition. Our results indicate that the structure, i.e. to which group the cluster belongs, and the openness towards external knowledge flows deliver merely unsystematic indications with regard to a cluster's overall success. Its ability to change composition towards a more balanced ratio of science and capital over time, on the other hand, turns out as a key explanatory factor. Hence, the dynamic perspective proves effective illuminating cluster growth and performance, where our explorative findings provide a promising avenue for further evolutionary research

Innovation modes and productivity in the UK

This paper is motivated by the aim to develop appropriate indicators capturing modes of innovation by UK enterprises, examine how such innovation practices vary across regions and industries and explore the extent to which they have an impact on productivity. There is an emphasis on identifying and examining the relevance of non-technological innovation that builds on and extends previous research in this important area. Traditionally, measures of innovation have rested on single indicators such as patenting or R&D, supplemented, by product and process and process innovation outputs. More recently innovations in management, organisational and marketing areas are being brought into the picture and the relevant information collected by innovation surveys. Among indicators of innovation the distinctions between technological and non-technological innovations has often been loosely translated into either activities in manufacturing versus services, or into product and process innovations versus organisational and marketing innovations. While these simplifications of technological and non-technological innovation can be a practically useful, since data is readily available, they do not fully recognize that mixed modes of innovations are adopted by today’s firms; firms whose environments are characterised by increased competition, internationalisation and shorter product life cycles

Mapping National Innovation Systems in the OECD Area

The purpose of this paper is to present new findings about the structure and the organization of innovative activities in selected OECD countries. By using the approach of national sys-tems of innovation as a conceptual framework and by applying multivariate data analysis techniques, this paper aims to add new insights into the specific structures of the eighteen national systems of innovation under study. A central result from this comparative study is a categorisation of national systems of innovation into different clusters, with each cluster rep-resenting distinctive cross-national structural similarities. By accounting for sectoral specif-ics, the commonly taken perspective on national innovation systems is extended. Thereby, a more precise picture of the structural composition of the analyzed national innovation sys-tems accrues. Also, a new linkage between the two approaches of national and sectoral inno-vation systems is created.national innovation systems, comparative study, classification

The Structure of Cluster Knowledge Networks Uneven, not Pervasive and Collective

This study focuses on the relationship between industrial clustering and innovation. It contributes to this literature by showing two empirical properties of the cluster learning process: first, that the structure of the knowledge network in a cluster is related with the heterogeneous distribution of firm knowledge bases and, second, that business interactions and inter-firm knowledge flows are not highly co-occurring phenomena. In particular, this paper highlights how the heterogeneity of firms’ knowledge bases generates uneven distribution of knowledge and selective inter-firm learning. This study has been based on empirical evidence collected at firm level in three wine clusters in Italy and Chile. Methods of social network analysis have been applied to process the data.Industrial clusters, knowledge flows, business interactions, networks.