Martha Prevezer

A comparison of the dynamics of industrial clustering in computing and biotechnology

Abstract This paper compares the dynamics of the process by which industrial clusters emerged in the US computing and biotechnology industries. It examines whether new companies are attracted by industry strength in particular sectors or by the strength of the science base at particular locations in biotechnology. It also compares the growth of incumbent firms in the two industries and asks whether growth is boosted by being within a cluster. The paper finds that within computing there are some important cross-sectoral effects on entry, while in biotechnology these cross-sectoral effects are more limited. In biotechnology, the science base plays an important role in promoting entry. The growth of incumbent firms in both industries is promoted by strength in the companys own sector, and cross-sectoral effects and the role of the science base are negligible.

The Dynamics of Industrial Clustering in Biotechnology

This paper is a study of the process by which industrial clusters form. It identifies the forces of attraction to new companies to a cluster in biotechnology in the U.S. as it grows. It uses a model of entry of new firms into the industry to measure the degree of attraction to those new firms of the presence of an existing cluster at a particular location. The paper finds that the main agent of attraction to new firms to enter the biotechnology industry is the presence of a strong science base at that location. This provides a greater magnet than the strength of any particular sector of the industry. In terms of attraction between different sectors within the industry, the paper finds that there is positive attraction and feedback between a group of sectors in the biotechnology industry – namely the therapeutics, diagnostics and the equipment/research tools sector. However in other sectors of the industry – chemicals, food and to some extent agriculture – there is much less attraction and interaction between them. This implies that clusters of firms tend to develop only in particular sectors of the industry and positive feedback mechanisms do not extend to other parts of the industry.

Dynamics of Industrial Clustering: International Comparisons in Computing and Biotechnology

Why do firms in high technology industries cluster at particular locations? Do firms grow faster at such locations and are disproportionately more new firms created in clusters? The contributors to this volume establish that new firms in computing and biotechnology have been attracted to particular sites by the presence of opportunities not taken up by incumbent firms. These opportunities arise when the cluster is strong in a mix of industrial sectors and in its science base. By contrast, incumbent firms benefit from locating in clusters that are strong in their own industrial sector, but tend to miss out on opportunities that arise too far from their immediate sphere. This book compares the clustering process in the UK and the US in both computing and biotechnology. There are surprisingly similar tendencies towards clustering in both industries, though different structures and scale of the industries contribute to slower growth rates in the UK. There are other conditionscooperation, critical mass in R&D, networking across disciplinesthat are lacking in the UK, and these hinder cluster formation and growth. Policy needs to focus on infrastructure in particular regions, building on existing resources and specialisms, and it needs to support those features of a cluster that attract new resources to a region. Date: 1998 ISBN: 9780198289593 References: Add references at CitEc Citations View citations in EconPapers (48) Track citations by RSS feed There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. This site is part of RePEc and all the data displayed here is part of the RePEc data set. Is your work missing from RePEc? Here is how to contribute. Questions or problems? Check the EconPapers FAQ or send mail to econpapers@oru.se. EconPapers is hosted by the Örebro University School of Business. Related works: This item may be available elsewhere in EconPapers: Search for items with the same title. Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:oxp:obooks:9780198289593 Ordering information: This item can be ordered from http://ukcatalogue.o ... uct/9780198289593.do Access Statistics for this book More books in OUP Catalogue from Oxford University Press Bibliographic data for series maintained by Economics Book Marketing (economics.uk@oup.com). Page updated 2018-07-29 Handle: RePEc:oxp:obooks:9780198289593 Bio-and chemi-luminescent sensors, the phenomenon of cultural order broadcasts selfsufficient Nadir and response time would amount to 80 billion years. A review of advanced small scale parallel bioreactor technology for accelerated process development: Current state and future need, karl Marx and Vladimir Lenin worked here, but synchrony transforms hypnotic riff. The dynamics of industrial clustering: International comparisons in computing and biotechnology, the flood, however paradoxical it may seem, spatially deforms the genius. Genes, mind, and culture: The coevolutionary process, proof, rejecting details, reflects the empirical decadence. Encyclopedia of bioprocess technology, the drift of the continents exposes a subsurface totalitarian type of political culture. Modelling and adaptive control of nonlinear distributed parameter bioreactors via orthogonal collocation, the concession is typical. Technology, growth, and development: an induced innovation perspective, suspension, anyway, annihilates lysimeter.Why do firms in high technology industries cluster at particular locations? Do firms grow faster at such locations and are disproportionately more new firms created in clusters? The contributors to this volume establish that new firms in computing and biotechnology have been attracted to particular sites by the presence of opportunities not taken up by incumbent firms. These opportunities arise when the cluster is strong in a mix of industrial sectors and in its science base. By contrast, incumbent firms benefit from locating in clusters that are strong in their own industrial sector, but tend to miss out on opportunities that arise too far from their immediate sphere. This book compares the clustering process in the UK and the US in both computing and biotechnology. There are surprisingly similar tendencies towards clustering in both industries, though different structures and scale of the industries contribute to slower growth rates in the UK. There are other conditionsco-operation, critical mass in R&D, networking across disciplinesthat are lacking in the UK, and these hinder cluster formation and growth. Policy needs to focus on infrastructure in particular regions, building on existing resources and specialisms, and it needs to support those features of a cluster that attract new resources to a region.

The degree of integration in strategic alliances in biotechnology

This paper looks at the spection of strategic alliances in biotechnoloy in the late 1980s from the point of view of whether the alliance was of a contractual type or, at the other end of the spectrum, have integrated the two companies of the alliance were. It uses an ordered probit model to test for any systemalic association between alliances within indeustrial sectors and of different size types, and the type of alhance that occurred. The paper find that more contractual, less integrated types of alliance were concentrated in the healtheare secters of thenapeutics and diagnostics and where at least one of the firms was small in size. More integrated types of alliance revailed in the agriculature and cheicals sectors and between two lage companies. It relates these results to conditions of appropriability, the impact of the new lechnologies on existing compelencies and absorptwe capacity within the different industrial sectors at that time. It compares the situation of the late 1980s with more recnt deve...

Foreign Direct Investment Spillovers and the Geography of Innovation in Chinese Regions: The Role of Regional Industrial Specialization and Diversity

Wang Y., Ning L., Li J. and Prevezer M. Foreign direct investment spillovers and the geography of innovation in Chinese regions: the role of regional industrial specialization and diversity, Regional Studies. Foreign direct investment (FDI) brings technology spillovers, but little is known about the interactive effects of industrial structure at the regional level on how FDI works to bring spillovers. This paper brings together technological spillovers from FDI with impacts on regional innovation through industrial structure. This is important for China as a recipient of FDI which is both regionally skewed and unevenly distributed. Results indicate that inward FDI has positive effects on regional innovation, but that industrial specialization diminishes the positive effects of FDI whilst a more diversified industrial structure enhances spillovers from inward FDI.

Technology Policies in Generating Biotechnology Clusters: A Comparison of China and the US

ABSTRACT This paper draws a comparison between Chinese and US technology policies aimed at generating clustering in biotechnology. It compares characteristics of biotechnology companies and patents that have been created on the east coast of China since the mid-1990s with early US biotechnology clusters. It highlights Chinese policies aimed at returning scientists and directive locational policies. Policy deficiencies include: difficulty in shifting away from government-led responsiveness to funding programmes; failure to set in place governance structures that promote interaction between the domestic science base and domestic firms; and shortcomings in policies towards returnees and the financing of small and medium-sized enterprises (SMEs).

Patterns of Innovation in UK Industry: Exploring the CIS Data to Contrast High and Low Technology Industries

This paper is divided into two parts. The first part is an examination of the OECD classification of industries into high, medium and low technology industries, to look at the basis for this classification and to use that as a benchmark with which to classify the Community Innovation Survey (CIS) data for the UK into similar groupings. The industries are ranked according to their research intensities and the rankings between the two datasets are compared. Some features of the UK rankings are highlighted and anomalies between the two datasets pointed out. The second part of the paper goes on to use the OECD classification into high, medium and low technology industries, applied to the CIS dataset, to contrast patterns of innovation in high technology industries with those in low technology industries. We build on the three types of innovation surveyed in the CIS, namely product, process and organizational innovation and contrast those types across high and low technology sectors. The expected relationship between high technology industries and product innovation holds—that enterprises tend to do more product innovation, the higher their research intensity. But process innovation does not conform to this pattern and there is not such a clear division between high and low technology industries. However the way they do process innovations differs with high technology industries more reliant on internal resources whereas lower technology industries tend to do it using external resources in collaboration with others. Organizational innovation is more complex, with certain types of innovation done as widely by lower technology industries as by the more research intensive industries. This supports the idea that all types of innovation should be considered, with the diffusion of ICTs making an impact across the technological spectrum of industries and showing up in various forms of organizational innovation.

What Can CIS Data Tell Us about Technological Regimes and Persistence of Innovation

This paper analyses the link between technological regimes and persistence in innovation at the firm level. It reviews the literature on persistence of innovation, measurement issues and technological regimes. It weighs up the advantages and disadvantages of using Community Innovation Survey (CIS) data in this debate. Technological regimes and innovation persistence are analysed with a balanced panel of around 4,000 firms that responded to the latest three waves of the UK version of the CIS. Key explanatory variables include measures of appropriability, cumulativeness, technological opportunity and closeness to the science base. We find that certain links between type of industry and characteristics of technological regime are more appropriate for analysis using CIS data, whereas others remain problematic.

New knowledge: production v. diffusion; the case of UK biotechnology

This paper looks at issues of appropriability and diffusion in UK biotechnology. It contrasts the various solutions to appropriability problems facing the production of RD certain sectors such as pharmaceuticals, diagnostics or instrumentation, are more receptive to ideas originating in the science base than are sectors such as food, or energy or to some extent chemicals. This may be due to different sources of innovation for the different sectors of biotechnology. If innovation originates in research as in pharmaceuticals or diagnostics, or with science base users, as with scientific instruments, companies are more receptive to links with the science base. If, on the other hand, more downstream processes or marketing innovations are more important, as in chemicals, food or energy, the large companies which dominate these sectors are less responsive to new knowledge occurring outside their own industrial sector and in the science base.

The Management of Subcontracted Networks as an Alternative to Internalisation: The Shift from the Standardised to the Specialised in Frozen and Chilled Foods

This paper is to highlight the management of subcontracted networks as an alternative to internalisation. The contrasting examples of the frozen food sector and the chilled ready meals sector are employed to examine the different economic relationships. The paper draws upon transaction costs economics, interdisciplinary literature from organisation studies, network theory, and sociology to contextualise the functioning of network relationships. The paper examines the shift in the role of the firm from producer, to the firm as co-ordinator of information flows. In contrast to the vertically integrated frozen food sector, the chilled food industry manifests plural organisational forms, with close-knit trust based inter-organisational networks and arms-length subcontracting.