Download The Geography of Networks and R&D Collaborations by Thomas Scherngell (auth.), Thomas Scherngell (eds.) PDF
By Thomas Scherngell (auth.), Thomas Scherngell (eds.)
The geography of networks and R&D collaborations, particularly the spatial measurement of interactions among enterprises appearing joint R&D, have attracted a burst of awareness within the final decade, either within the clinical learn of the networks and within the coverage quarter. the quantity is meant to assemble a range of articles offering novel theoretical and empirical insights into the geographical dynamics of such networks and R&D collaborations, utilizing new, systematic info resources and utilizing state of the art spatial research and spatial econometric suggestions. It includes a piece on analytic advances and technique and thematic sections on constitution and spatial features of R&D networks and the influence of R&D networks and coverage implications. The edited quantity presents a set of high-level examine contributions with an target to give a contribution to the hot debate in monetary geography and nearby technology on how the constitution of formal and casual networks modifies and impacts the spatial and temporal diffusion of knowledge.
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De Montis et al. of workers and students, by applying grouping methodologies based on the characterisation of the Sardinian commuters’ system as a complex weighted network. 1 Introduction Over the last 15 years there has been a great scientific interest in complex network analysis, a method able to characterize systems with a very large number of entities (the nodes or vertices) interlinked by a series of connections/relationships (the links or edges). The objects of this analysis have regarded biological systems (predatorpray); information systems (Internet); sociological systems; and transportation systems (railway and road networks).
They demonstrated that stability and efficiency is clearly dependent upon the cost of R&D collaborations and the topology of the network. The authors also argued that “the complete graph is stable in small industries and for low collaboration costs, while the class of sizehomogeneous disconnected cliques and the star are stable in large industries” (Ko¨nig et al. 2012, p. 707). Smith-Doerr et al. (2004) scrutinised the social network of project managers belonging to the R&D laboratory of a Fortune 500 company and leading six projects.
Another case is that of large networks for which nodes have various levels of organization. e. a community may include recursively other smaller communities. In this case the community structure is characterized by a hierarchical structure (Sales-Pardo et al. 2007). In the literature, we can find three main classes of methods: divisive algorithms, optimization methods, and spectral methods. Alternative approaches that do not fit in the above classification are the following: clique percolation, random walk, maximum likelihood, Q-state Potts model, Markov cluster algorithm, and L-shell method (see Fortunato 2010).