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Innovation, Spillovers and University-Industry Collaboration: An Extended Knowledge Production Function Approach

TL;DR: In this paper, the effect of knowledge spillovers from academic research on regional innovation is analyzed using an extended knowledge production function framework applied to regions in the Netherlands, and it is shown that the impact of academic research is not only mediated by geographical proximity but also by networks stemming from university-industry collaboration.
Abstract: This article analyses the effect of knowledge spillovers from academic research on regional innovation. Spillovers are localized to the extent that the underlying mechanisms are geographically bounded. However, university-industry collaboration - as one of the carriers of knowledge spillovers - is not limited to the regional scale. Consequently, we expect spillovers to take place over longer distances. The effect of university-industry collaboration networks on knowledge spillovers are modelled using an extended knowledge production function framework applied to regions in the Netherlands. We find that the impact of academic research on regional innovation is not only mediated by geographical proximity but also by networks stemming from university-industry collaboration.
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Journal ArticleDOI
TL;DR: In this article, the authors proposed a composite indicator that measures the regional degree of exposure to external knowledge sources, which can be used to appraise the extent to which each region is in an optimal position to access external innovative resources.
Abstract: The aim of this study was to devise a method for computing a composite indicator that measures the regional degree of exposure to external knowledge sources. On the basis of this indicator, we propose a typology of regions according to their potential capacity to access extra-local items of knowledge, which might help them to recombine complementary elements of such an asset to produce a higher number of new ideas. Building on various research streams that have been relatively independent to date, we summarize a nonexhaustive instrumental list of recent studies that motivates our approach and the construction of our complex indicator, which can be used to appraise the extent to which each region is in an optimal position to access external innovative resources.

50 citations

Journal ArticleDOI
TL;DR: In this paper, a conceptual framework is proposed to explain the differences between innovation systems and their geography by drawing on elements of endogenous growth, new economic geography and regional innovation systems. But the authors do not consider the differences in innovative capacity between the European Union (EU), the United States (US), China and India as emerging competitors for international technological leadership.
Abstract: This paper discusses recent developments in the literature on local and regional innovative performance to show how an ‘integrated’ conceptual framework based on the cross-fertilization of different theories can serve as a foundation for the comparative analysis of territorial innovation dynamics in both developed and developing countries. The paper outlines a conceptual framework to explain the differences between innovation systems and their geography by drawing on elements of endogenous growth, new economic geography and regional innovation systems. This framework forms the basis of the subsequent analysis of the differences in innovative capacity between the European Union (EU), the United States (US) – as the leader system to be challenged – and China and India as emerging competitors for international technological leadership. The systematic analysis of a large body of empirical literature shows important differences between the spatial patterning of ‘emerging’ (China and India) and ‘mature’ (EU and US) innovation systems.

44 citations

Journal ArticleDOI
TL;DR: In this paper, the role of different types of proximity on the technological activity of a region within the context of a knowledge production function where R&D expenditure and human capital are the main internal inputs.
Abstract: This paper aims at investigating the role of different types of proximity on the technological activity of a region within the context of a knowledge production function where R&D expenditure and human capital are the main internal inputs. We intend to assess if, and how much, the creation of new ideas in a certain region is the result of knowledge flows coming from proximate regions. In particular, we examine in detail the concept of proximity combining the usual geographical dimension with the institutional, technological, social and organizational proximity. The analysis is implemented for an ample dataset referring to 276 regions in 29 European countries (EU27 plus Norway, Switzerland) for the last decade. Results show that human capital and R&D are clearly essential for innovative activity but with an impact which is much higher for the former factor. As for the proximity and network effects, we find that geography is important but less than technological and cognitive proximity. Social and organizational networks are also relevant although their role is modest.

39 citations

Journal ArticleDOI
TL;DR: In this paper, an econometric model of population{employment dynamics in which sectoral variations in economic development are explicitly taken into account is applied to a large urban planning policy proposal in The Netherlands, and empirical analyses suggest that population dynamics are largely exogenous, population changes drive employment in particular in the industry and retail sectors, and employment in all sectors depends strongly on intersectoral dynamics.
Abstract: An important subset of the literature on agglomeration externalities hypothesizes that intrasectoral and intersectoral relations are endogenously determined in models of local and regional economic growth. Remarkably, structural adjustment models describing the spatio-temporal dynamics of population and employment levels or growth traditionally do not include intersectoral economic dynamics. This paper argues and shows that allowing for economic linkages across sectors in these models adds considerable value, especially in forecasting. An econometric model of population{employment dynamics in which sectoral variations in economic development are explicitly taken into account is applied to a large urban planning policy proposal in The Netherlands. The empirical analyses suggest that population dynamics are largely exogenous, population changes drive employment in particular in the industry and retail sectors, and employment in all sectors depends strongly on intersectoral dynamics. Intersectoral dynamics appear as important drivers of regional sectoral employment changes; they are even more important than population changes, and their eect shows up clearly even within the Dutch institutional context where strict regulatory housing and planning restrictions are enforced.

35 citations

Journal ArticleDOI
TL;DR: In this article, a Bayesian spatial Markov Chain Monte Carlo model composition (MC3) analysis of growth rates in European regional patenting activity is provided, which identifies a large set of candidate explanatory variables that characterize regional stocks of knowledge, including: human resources devoted to innovative activity, scientific and technical capabilities, public and private investments, government policies, as well as regional industry structure.
Abstract: We provide a Bayesian spatial Markov Chain Monte Carlo model composition (MC3) analysis of growth rates in European regional patenting activity. Based on theoretical models on innovation and growth, we identify a large set of candidate explanatory variables that characterize regional stocks of knowledge, including: human resources devoted to innovative activity, scientific and technical capabilities, public and private investments, government policies, as well as regional industry structure, and indicators of regional technology gaps that reflect distance from the technological frontier. Our analysis shows that accommodating spatial dependence and heterogeneity leads to different conclusions regarding factors important for technological transfer and knowledge spillovers.

25 citations