Universities, knowledge networks and regional policy

As knowledge becomes an increasingly important part of regional innovation and development processes, the role of universities has come to the fore of regional innovation and economic development policy The objective of this paper is to critically review and assess the structure and function of knowledge networks and modes of engagement between universities and the business community in regional settings and contexts. It is argued that while regional knowledge networks and modes of engagement between universities and the business community are becoming increasingly prevalent, it is often difficult to ascribe investments in knowledge-based infrastructure to improved regional competitiveness. It is concluded that in a globalised knowledge environment the engagement between universities and regional business communities must be based on a mutual understanding of the role of both network and market-based knowledge interactions

Shaping the formation of university-industry research collaborations: what type of proximity does really matter?

Research collaborations between universities and industry (U-I) are considered to be one important channel of potential localized knowledge spillovers (LKS). These collaborations favour both intended and unintended flows of knowledge and facilitate learning processes between partners from different organizations. Despite the copious literature on LKS, still little is known about the factors driving the formation of U-I research collaborations and, in particular, about the role that geographical proximity plays in the establishment of such relationships. Using collaborative research grants between universities and business firms awarded by the UK Engineering and Physical Sciences Research Council (EPSRC), in this article we disentangle some of the conditions under which different kinds of proximity contribute to the formation of U-I research collaborations, focusing in particular on clustering and technological complementarity among the firms participating in such partnerships

Conceptualizing the Role of Geographical Proximity in Project Based R&D Networks: A Literature Survey

Empirical evidence shows that research is being carried out more in cooperation or in collaboration with others, and the networks described by these collaborative research activities are becoming more and more complex. This phenomenon brings about new strands of research questions and opens up a different research context in the area of geography of innovation. The recent set of literature addressing these new issues shows a high degree of variation in terms of focus, approaches and methodology. Hence to elucidate the relationship between networks and geography it is crucial to have a review them. In this regard, this study focuses on a particular type of networks, namely, project based R&D networks and aims at describing the state-of-the-art in explaining the specificity of geography in formation and evolution of such networks. Towards this aim, we framed the discussion along four lenses: the specificity of geography in partner choice, in successful execution of the collaboration, in the resulting innovation performance both at the organizational and regional level, and the spatio-temporal evolution of networks. The overview provided by the survey is suggestive regarding the theorization of geography and network relationship, and informative regarding the issues demanding further research effort, and promising extensions.

When does centrality matter? Scientific productivity and the moderating role of research specialization and cross-community ties

The present study addresses the ongoing debate concerning academic scientific productivity. Specifically, given the increasing number of collaborations in academia and the crucial role networks play in knowledge creation, we investigate the extent to which building social capital within the academic community represents a valuable resource for a scientist's knowledge-creation process. We measure the social capital in terms of structural position within the academic collaborative network. Furthermore, we analyse the extent to which an academic scientist's research specialization and ties that cross-community boundaries act as moderators of the aforementioned relationship. Empirical results derived from an analysis of an Italian academic community from 2001 to 2008 suggest academic scientists that build social capital by occupying central positions in the community outperform their more isolated colleagues. However, scientific productivity declines beyond a certain threshold value of centrality, hence revealing the existence of an inverted U-shaped relationship. This relationship is negatively moderated by the extent to which an academic focuses research activities in few scientific knowledge domains, whereas it is positively moderated by the number of cross-community ties established

Innovation, generative relationships and scaffolding structures: implications of a complexity perspective to innovation for public and private interventions

The linear model of innovation has been superseded by a variety of theoretical models that view the innovation process as systemic, complex, multi-level, multi-temporal, involving a plurality of heterogeneous economic agents. Accordingly, the emphasis of the policy discourse has changed over time. The focus has shifted from the direct public funding of basic research as an engine of innovation, to the creation of markets for knowledge goods, to, eventually, the acknowledgement that knowledge transfer very often requires direct interactions among innovating actors. In most cases, policy interventions attempt to facilitate the match between “demand” and “supply” of the knowledge needed to innovate. A complexity perspective calls for a different framing, one focused on the fostering of processes characterized by multiple agency levels, multiple temporal scales, ontological uncertainty and emergent outcomes. This contribution explores what it means to design interventions in support of innovation processes inspired by a complex systems perspective. It does so by analyzing two examples of coordinated interventions: a public policy funding innovating networks (with SMEs, research centers and university), and a private initiative, promoted by a network of medium-sized mechanical engineering firms, that supports innovation by means of technology brokerage. Relying on two unique datasets recording the interactions of the organizations involved in these interventions, social network analysis and qualitative research are combined in order to investigate network dynamics and the roles of specific actors in fostering innovation processes. Then, some general implications for the design of coordinated interventions supporting innovation in a complexity perspective are drawn

Geographical co-location, social networks and inter-firm marketing co-operation : the case of the salmon industry

This study looks at the factors that influence the development of marketing co-operation among cluster-based firms. It examines data from SMEs operating within the salmon farming industry in two different regions: Scotland and Chile. Analyses indicate that informal social networks help explain the observed relationship between geographical proximity and inter-firm marketing co-operation, especially for firms located in peripheral rural communities. A theoretical model is proposed for further research in the field that, until recently, has been traditionally analysed only by economists. Practical implications are suggested for practitioners and policymaker

Why Do Business Service Firms Cluster? Small Consultancies, Clustering and Decentralisation in London and Southern England

Notwithstanding their remarkable recent growth, surprisingly little research has hitherto been conducted on the evolving geography of professional and business services in Britain. This paper analyses the results of a detailed survey of 300 small and medium-sized management and engineering consultancies, in investigating the forces underpinning both the striking clustering of such firms in central London and their growth in decentralised locations of East Anglia and South West England. Particular attention is paid to the role of demand-side influences, localised 'collective learning' processes, and increasing globalisation in clustering, and to so called 'enterprising behaviour theory' in explaining decentralisation.business services, clustering London, globalisation, SMEs, collective learning

Research Networks and Inventors’ Mobility as Drivers of Innovation: Evidence from Europe

We investigate the importance of the labour mobility of inventors, as well as the scale, extent and density of their collaborative research networks, for regional innovation outcomes. To do so, we apply a knowledge production function framework at the regional level and include inventors’ networks and their labour mobility as regressors. Our empirical approach takes full account of spatial interactions by estimating a spatial lag model together, where necessary, with a spatial error model. In addition, standard errors are calculated using spatial heteroskedasticity and autocorrelation consistent estimators to ensure their robustness in the presence of spatial error autocorrelation and heteroskedasticity of unknown form. Our results point to the existence of a robust positive correlation between intra-regional labour mobility and regional innovation, whilst the relationship with networks is less clear. However, networking across regions positively correlates with a region’s innovation intensity.Speed Limits; inventors’ mobility, networks of co-inventors, knowledge production function, spatial econometrics, European regions

Shaping the formation of university-industry research collaborations: what type of proximity does really matter?

Research collaborations between universities and industry (U-I) are considered to be one important channel of potential localised knowledge spillovers. These collaborations favour both intended and unintended flows of knowledge and facilitate learning processes between partners from different organisations. Despite the copious literature on localised knowledge spillovers, still little is known about the factors driving the formation of U-I research collaborations and, in particular, about the role that geographical proximity plays in the establishment of such relationships. Using collaborative research grants between universities and business firms awarded by the UK Engineering and Physical Sciences Research Council (EPSRC), in this paper we disentangle some of the conditions under which different kinds of proximity contribute to the formation of U-I research collaborations, focussing in particular on technological complementarity among the firms participating in such partnerships.university-industry research collaborations, proximity, geography, industrial clustering, technological complementarity

Standard-Setting and Knowledge Dynamics in Innovation Clusters

Extensive research has been conducted on how firms and regions take advantage of spatially concentrated assets, and also why history matters to regional specialisation patterns. In brief, it seems that innovation clusters as a distinctive regional entity in international business and the geography of innovation are of increasing importance in STI policy, innovation systems and competitiveness studies. Recently, more and more research has contributed to an evolutionary perspective on collaboration in clusters. Nonetheless, the field of cluster or regional innovation systems remains a multidisciplinary field where the state of the art is determined by the individual perspective (key concepts could, for example, be industrial districts, innovative clusters with reference to OECD, regional knowledge production, milieus & sticky knowledge, regional lock-ins & path dependencies, learning regions or sectoral innovation systems). According to our analysis, the research gap lies in both quantitative, comparative surveys and in-depth concepts of knowledge dynamics and cluster evolution. Therefore this paper emphasises the unchallenged in-depth characteristics of knowledge utilisation within a cluster's collaborative innovation activities. More precisely, it deals with knowledge dynamics in terms of matching different agents´ knowledge stocks via knowledge flows, common technology specification (standard-setting), and knowledge spillovers. The means of open innovation and system boundaries for spatially concentrated agents in terms of knowledge opportunities and the capabilities of each agent await clarification. Therefore, our study conceptualises the interplay between firm- and cluster-level activities and externalities for knowledge accumulation but also for the specification of technology. It remains particularly unclear how, why and by whom knowledge is aligned and ascribed to a specific sectoral innovation system. Empirically, this study contributes with several descriptive calculations of indices, e.g. knowledge stocks, GINI coefficients, Herfindahl indices, and Revealed Patent Advantage (RPA), which clearly underline a high spatial concentration of both mechanical engineering and biotechnology within a European NUTS2 sample for the last two decades. Conceptually, our paper matches the geography of innovation literature, innovation system theory, and new ideas related to the economics of standards. Therefore, it sheds light on the interplay between knowledge flows and externalities of cluster-specific populations and the agents' use of such knowledge, which is concentrated in space. We find that knowledge creation and standard-setting are cross-fertilising each other: although the spatial concentration of assets and high-skilled labour provides new opportunities to the firm, each firm's knowledge stocks need to be contextualised. The context in terms of 'use case' and 'knowledge biography' makes technologies (as represented in knowledge stocks) available for collaboration, but also clarifies relevance and ownership, in particular intellectual property concerns. Owing to this approach we propose a conceptualisation which contains both areas with inter- and intra-cluster focus. This proposal additionally concludes that spatial and technological proximity benefits standard-setting in high-tech and low-tech industries in very different ways. More precisely, the versatile tension between knowledge stocks, their evolution, and technical specification & implementation requires the conceptualisation and analysis of a non-linear process of standard-setting. Particularly, the use case of technologies is essential. Related to this approach, clusters strongly support the establishment of technology use cases in embryonic high-tech industries. Low-tech industries in contrast rather depend on approved knowledge stocks, whose dynamics provide better and fast accessible knowledge inputs within low-tech clusters.innovation clusters, standard-setting, knowledge externalities and flows, knowledge alignment, mechanical engineering, biotechnology