1,721,207 research outputs found

    Deconstructing clusters: chaotic concept or policy panacea?

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    Over the past decade, there has been growing interest in local industrial agglomeration and specialization, not only by economic geographers but also by economists and by policy-makers. Of the many ideas and concepts to have emerged from this new-found focus, Michael Porter's work on ‘clusters’ has proved by far the most influential. His ‘cluster theory’ has become the standard concept in the field, and policy-makers the world over have seized upon Porter's cluster model as a tool for promoting national, regional, and local competitiveness, innovation and growth. But the mere popularity of a construct is by no means a guarantee of its profundity. Seductive though the cluster concept is, there is much about it that is problematic, and the rush to employ ‘cluster ideas’ has run ahead of many fundamental conceptual, theoretical and empirical questions. Our aim is to deconstruct the cluster concept in order to reveal and highlight these issues. Our concerns relate to the definition of the cluster concept, its theorization, its empirics, the claims made for its benefits and advantages, and its use in policy-making. Whilst we do not wish to debunk the cluster idea outright, we do argue for a much more cautious and circumspect use of the notion, especially within a policy context: the cluster concept should carry a public policy health warning. <br/

    Making history matter more in evolutionary economic geography

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    Our focus in this paper is on a somewhat curious feature of evolutionary economic geography, namely that although concerned with evolution – with processes of historical change and transformation – evolutionary economic geography seems not to take history as seriously as it would be expected to do. We argue that evolutionary economic geography is inescapably an historical social science, and that as such would benefit from exploring the different ways in which history can be used in causal investigation, from problematising the different temporalities of economic change and transformation, and from giving more attention to appreciative theorising and narrative case study over variable-centred approaches

    Place and industrial development: Paths to understanding?

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    The speed and extent of change in the geographical distribution of industry in recent history, both within and between nations, has been unprecedented. The growth of globalization has reordered the global distribution of manufacturing and the continuing development of digitalization, and artificial intelligence (AI) may well change the spatial and global distribution of both manufacturing and service industries in a similarly profound way . Among these radical spatial shifts, however, place continues to matter for industrial development. The development and evolution of firms and places are deeply entangled, so that location continues to shape the capabilities and resources available to industries, sometimes positively, in other cases negatively. Indeed, in an effort to capture and stabilize this shifting industrial landscape, modern official industrial strategy in many countries increasingly seeks to use ‘place’ as a platform on which to base policy measures that respond to industries’ place-specific needs. The continuing significance of place in industrial development is not easy to explain, however, as it involves the locally varying and locally specific interaction of a series of complex processes that together produce the emergence and development of the assets and capabilities of firms and institutional actors (Scott, 1998). Recent years have seen the growth of an evolutionary path-based approach to understanding these effects and the significance of place for industrial development, and this chapter provides a critical review of the ‘path approach’ and its progress so far

    Conceptualizing cluster evolution: beyond the life cycle model?

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    Although the literature on the evolution of industrial clusters is not vast, a preferred approach has already become evident based around the idea of a cluster ‘life cycle’. This approach has several limitations. This paper explores a different conception of cluster evolution, drawing on the ‘adaptive cycle’ model that has been developed in evolutionary ecology. Using this model, cluster evolution is viewed as an adaptive process with different possible outcomes based on episodic interactions of nested systems. Though not without limitations, this approach offers greater scope as a framework for shaping the research agenda into the evolution of clusters

    Taking risks in regions: the geographical anatomy of europe’s emerging venture capital market

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    Over the past 25 years, the USA has pioneered a new technological revolution, based on large numbers of new small enterprises, financed by a dynamic venture (risk) capital market. The European Union, meanwhile, has lagged behind in this sector of economic activity, and compared to the US innovative small and medium enterprises appear to find it more difficult to get started and grow. At a time when regional and local banking systems - traditionally major sources of capital for small and medium sized enterprises across Europe - are undergoing intense reorganisation and restructuring, the European Commission considers the development of a substantial risk capital market to be a key condition for closing the 'enterprise gap' with the US. While the venture capital industry is much less developed in Europe than it is in the US, nevertheless it has recently experienced a marked increase in activity. But whereas the European Commission argues that venture capital activity needs to be much more regionally clustered if it is to emulate the US experience, the OECD and some EU member states have argued for a more even regional distribution. The aim of the paper is to chart the growth and geographical anatomy of the emerging European venture capital market, and to examine its spatial development and regional implications in the context of these somewhat opposing views
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