The spatial component of R&D networks

We study the role of geography in R&D networks by means of a quantitative, micro-geographic approach. Using a large database that covers international R&D collaborations from 1984 to 2009, we localize each actor precisely in space through its latitude and longitude. This allows us to analyze the R&D network at all geographic scales simultaneously. Our empirical results show that despite the high importance of the city level, transnational R&D collaborations at large distances are much more frequent than expected from similar networks. This provides evidence for the ambiguity of distance in economic cooperation which is also suggested by the existing literature. In addition we test whether the hypothesis of local buzz and global pipelines applies to the observed R&D network by calculating well-defined metrics from network theory.Comment: Working paper, 22 pages, 7 figure

The Dynamics of Interfirm Networks along the Industry Life Cycle: The Case of the Global Video Games Industry 1987-2007

In this paper, we study the formation of network ties between firms along the life cycle of a creative industry. We focus on three drivers of network formation: i) network endogeneity which stresses a path-dependent change originating from previous network structures, ii) five forms of proximity (e.g. geographical proximity) which ascribe tie formation to the similarity of actors' attributes; and (iii) individual characteristics which refer to the heterogeneity in actors capabilities to exploit external knowledge. The paper employs a stochastic actor-oriented model to estimate the - changing - effects of these drivers on inter-firm network formation in the global video game industry from 1987 to 2007. Our findings indicate that the effects of the drivers of network formation change with the degree of maturity of the industry. To an increasing extent, video game firms tend to partner over shorter distances and with more cognitively similar firms as the industry evolves.network dynamics, industry life cycle, proximity, creative industry, video game industry, stochastic actor-oriented model

Geo-cultural influences and critical factors in inter-firm collaboration

Inter-firm collaboration and other forms of inter-organisational activity are increasingly the means by which technological innovation occurs. This paper draws on evidence from two studies of the same set of firms to examine the conduct of collaborations over time across different contexts. The purpose is to examine the critical factors associated with successful collaboration and explore the importance of the geo-cultural context in understanding the conduct of inter-firm collaboration. The conceptual framework draws on two main sources: - Storper’s concept of ‘conventions’ of identity and participation and Lorenz’s classification of different types of knowledge. These are used to indicate the kinds and sources of adjustments required for successful collaboration

Innovation, spillovers, and university-industry collaboration: An extended knowledge production function approach

This paper 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 is 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 mediated not only by geographical proximity but also by social networks stemming from collaboration networks.knowledge production function, knowledge spillovers, university-industry collaboration, innovation, social networks

Collaboration in sensor network research: an in-depth longitudinal analysis of assortative mixing patterns

Many investigations of scientific collaboration are based on statistical analyses of large networks constructed from bibliographic repositories. These investigations often rely on a wealth of bibliographic data, but very little or no other information about the individuals in the network, and thus, fail to illustrate the broader social and academic landscape in which collaboration takes place. In this article, we perform an in-depth longitudinal analysis of a relatively small network of scientific collaboration (N = 291) constructed from the bibliographic record of a research center involved in the development and application of sensor network and wireless technologies. We perform a preliminary analysis of selected structural properties of the network, computing its range, configuration and topology. We then support our preliminary statistical analysis with an in-depth temporal investigation of the assortative mixing of selected node characteristics, unveiling the researchers' propensity to collaborate preferentially with others with a similar academic profile. Our qualitative analysis of mixing patterns offers clues as to the nature of the scientific community being modeled in relation to its organizational, disciplinary, institutional, and international arrangements of collaboration.Comment: Scientometrics (In press

Data-driven modeling of collaboration networks: A cross-domain analysis

We analyze large-scale data sets about collaborations from two different domains: economics, specifically 22.000 R&D alliances between 14.500 firms, and science, specifically 300.000 co-authorship relations between 95.000 scientists. Considering the different domains of the data sets, we address two questions: (a) to what extent do the collaboration networks reconstructed from the data share common structural features, and (b) can their structure be reproduced by the same agent-based model. In our data-driven modeling approach we use aggregated network data to calibrate the probabilities at which agents establish collaborations with either newcomers or established agents. The model is then validated by its ability to reproduce network features not used for calibration, including distributions of degrees, path lengths, local clustering coefficients and sizes of disconnected components. Emphasis is put on comparing domains, but also sub-domains (economic sectors, scientific specializations). Interpreting the link probabilities as strategies for link formation, we find that in R&D collaborations newcomers prefer links with established agents, while in co-authorship relations newcomers prefer links with other newcomers. Our results shed new light on the long-standing question about the role of endogenous and exogenous factors (i.e., different information available to the initiator of a collaboration) in network formation.Comment: 25 pages, 13 figures, 4 table

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.