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The main focus in this chapter is on knowledge spillovers between high-technology firms in Europe, as captured by patent citations. High-technology is defined to include the ISIC sectors aerospace (ISIC 3845), electronics-telecommunication (ISIC 3832), computers and office equipment (ISIC 3825), and pharmaceuticals (ISIC 3522). The European coverage is given by patent applications at the European Patent Office that are assigned to hightechnology firms located in the EU-25 member states (except Cyprus and Malta), the two accession countries Bulgaria and Romania, and Norway and Switzerland. By following the paper trail left by citations between these high-technology patents, the contribution provides strong evidence for the localisation of knowledge spillovers at two different levels (country, region) in Europe even after controlling for the tendency of inventive activities in the high-technology sector to be geographically clustered. The findings not only indicate that knowledge localisation exists in the aggregate, but also that there are variations of localisation by region.

Despite a growing body of empirical evidence that demonstrates the nature of spatial variations in innovation and the adoption of new technologies, at the time this chapter was written few studies had been conducted in such a way as to enable direct comparisons between different countries, either to establish international differences in innovative performance or to identify differences in regional patterns in different national contexts, particularly between EC and non-EC countries within Europe. In this paper the results of recent surveys of comparable industries in Great Britain and Austria are used to begin to address this issue, with particular attention to some of the inherent difficulties in undertaking such comparisons. By using a mixture of simple cross-tabulations and multivariate logit models, differences between the two countries in the adoption of a number of new process technologies based upon microelectronics in the spheres of manufacturing production, design, and co-ordination are identified. It is suggested that, not only does Austria lag Great Britain in the introduction of new technology, but that variations between similar types of region are more pronounced and entrenched in Austria at that time.

Over the past two decades Austria’s export-driven electronics industry has experienced a progressive territorial distribution that has substantially decentralised production and employment. Nevertheless, the capital region’s concentration has provided many advantages to R&D-intensive establishments through subcontractual opportunities and better access to advanced research and production skills. This paper analyses the relationship between R&D, territorial location and the most important organisational characteristics in Austria’s electronics industries. An assessment of operational motivations, based on establishment-level survey data, is followed by a factor analysis that reveals the main organisational dimensions. Statistical analyses of the association between R&D intensity, territorial location and the organisational factors are then expanded to consider subcontracting and just-in-time production methods. Two-way subcontracting, whereby firms both subcontract part of their production out and are in turn contracted by others, is found to be prevalent. Such arrangements are thought to help firms specialise and avoid implementing costly production techniques whilst helping save capital and resources that can be reinvested in R&D. These analyses provide important insights on the association between R&D and subcontracting, just-in-time production and on the advantages of skilled production labour and plant size for research-intensive manufacturing establishments.

The chapter analyses the potential impact of technological progress in information processing on the size of retail markets. The analysis — restricted to a single commodity market with uncertain demand — shows that the ability of firms to process information and predict demand may affect the characteristics of retail markets. The results, moreover, indicate that risk-averse firms always devote resources to demand forecasting, producers are better off trading with retailers than with final consumers, and the volume of output supplied through retail markets is greater than it would be if producers traded directly with consumers.

This chapter connects the knowledge based economy with the formation of networks, a field that constitutes a moving target. Networks have certainly not ceased to develop, if anything it is the hierarchical organisation that is in retreat. The literature reviewed in this chapter reflects this state of things. It is not a literature on phenomena that has reached equilibrium, but one that is vigorously developing. Clearly, to review such an expanding field constitutes an almost impossible task, at least for what concerns completeness of coverage. Thus, the author has deliberately chosen to address the main problems and to cover the main classes of literature. The main points about the economics of knowledge are stated in Section 2, and the literature on networks is surveyed in Sections 3 to 5. The final section points to the new role of government that is emerging as the knowledge-driven and globalising economy alters the way firms organise their operation within and across nation states.

This chapter continues to contribute to our understanding of both the innovation process and the process of network formation by emphasising that the interactive nature of the innovation process has broken down the distinction between innovation and diffusion so that the creation of knowledge and its assimilation via networks are part of a single process. The discussion is enriched with empirical evidence from a comprehensive questionnaire of manufacturing firms in the metropolitan region of Vienna. The study confirms the vital importance of customer and user producer linkages and co-operation in the pre-competitive stage of the innovation process.

The relationship between university and industry is a complex and heterogeneous phenomenon, and an important topic of the recent debate on innovation systems. This chapter explores the role of knowledge flows between universities and firms in the Austrian national innovation system and provides valuable insights into several dimensions of knowledge flows that are not typically explored in research on this topic. The patterns of interaction between 46 different fields of science and 49 economic sectors represent an important and interesting outcome of the analysis. Left censored Tobit models are used to evaluate the effect of sector specific and science field specific characteristics upon the probability of knowledge interaction, disaggregated by type of interaction.

This chapter critically reviews the systems of innovation approach as a flexible and useful conceptual framework for spatial innovation analysis. It presents an effort to develop some missing links and to decrease the conceptual noise often present in the discussions on national innovation systems. The paper specifies elements and relations that seem to be essential to the conceptual core of the framework and argues that there is no a priori reason to emphasise the national over the subnational (regional) scale as an appropriate mode for analysis, irrespective of time and place. Localised input-output relations between the actors of the system, knowledge spillovers and their untraded interdependencies lie at the centre of the argument.

The relationship between knowledge spillovers and space is extremely complex and, at the current state of research, only partially understood. This is partly due to the fact that knowledge spillovers are difficult to measure. The chapter makes a modest attempt to shed some light on the role of space in the creation of technological knowledge in Austria. The study is exploratory rather than explanatory in nature and based on descriptive and exploratory techniques such as Moran’s I test for spatial autocorrelation and the Moran scatterplot. Clusters of the output of the knowledge creation process (measured in terms of patent counts) are compared with spatial concentration patterns of two input measures of knowledge production: private R&D and academic research. In addition, employment in manufacturing is considered to capture agglomeration economies. The analysis is based on data aggregated for two-digit ISIC industries and at the level of Austrian political districts. It explores the extent to which knowledge spillovers are mediated by spatial proximity in Austria. A time-space comparison makes it possible to study whether divergence or convergence processes in knowledge creation have occurred in the past two decades. As in the case of any exploratory data analysis, the findings need to be treated with caution and should be viewed only as an initial pre-modelling stage for Chapter 11.

This chapter provides some evidence on the importance of geographically mediated knowledge spillovers from university research activities to regional knowledge production in high-technology industries in Austria. Spillovers occur because knowledge created by universities has some of the characteristics of public goods, and creates value for firms and other organisations. The chapter lies in the research tradition that finds thinking in terms of a production function of knowledge useful and looks for patents as a proxy of the output of this process, while university research and corporate R&D investment represent the input side. It refines the classical regional knowledge production function by introducing a more explicit measure to capture the pool of relevant spatial academic knowledge spillovers. A spatial econometric approach is used to test for the presence of spatial effects and — when needed — to implement models that include them explicitly. The empirical results confirm the presence of geographically mediated university spillovers that transcend the spatial scale of political districts. They, moreover, demonstrate that such spillovers follow a clear distance decay pattern.