Clustering networked funded European research activities through rank-size laws

This paper treats a well-established public evaluation problem, which is the analysis of the funded research projects. We specifically deal with the collection of the research actions funded by the European Union over the 7th Framework Programme for Research and Technological Development and Horizon 2020. The reference period is 2007–2020. The study is developed through three methodological steps. First, we consider the networked scientific institutions by stating a link between two organizations when they are partners in the same funded project. In doing so, we build yearly complex networks. We compute four nodal centrality measures with relevant, informative content for each of them. Second, we implement a rank-size procedure on each network and each centrality measure by testing four meaningful classes of parametric curves to fit the ranked data. At the end of such a step, we derive the best fit curve and the calibrated parameters. Third, we perform a clustering procedure based on the best-fit curves of the ranked data for identifying regularities and deviations among years of research and scientific institutions. The joint employment of the three methodological approaches allows a clear view of the research activity in Europe in recent years

Phase transitions for the cavity approach to the clique problem on random graphs

We give a rigorous proof of two phase transitions for a disordered system designed to find large cliques inside Erdos random graphs. Such a system is associated with a conservative probabilistic cellular automaton inspired by the cavity method originally introduced in spin glass theory.Comment: 36 pages, 4 figure

Measuring network resilience through connection patterns

Networks are at the core of modeling many engineering contexts, mainly in the case of infrastructures and communication systems. The resilience of a network, which is the property of the system capable of absorbing external shocks, is then of paramount relevance in the applications. This paper deals with this topic by advancing a theoretical proposal for measuring the resilience of a network. The proposal is based on the study of the shocks propagation along the patterns of connections among nodes. The theoretical model is tested on the real-world instances of two important airport systems in the US air traffic network: Illinois (including the hub of Chicago) and New York states (with JFK airport)

Technology transfer in innovation networks: An empirical study of the enterprise Europe network

This article offers a network perspective on the collaborative effects of technology transfer, providing a research methodology based on the network science paradigm. We argue that such an approach is able to map and describe the set of entities acting in the technology transfer environment and their mutual relationships. We outline how the connections’ patterns shape the organization of the networks by showing the role of the members within the system. By means of a case study of a transnational initiative aiming to support the technology transfer within European countries, we analyse the application of the network science approach, giving evidence of its relative implications

A network science approach to inter-organizational innovation networks: the case study of Enterprise Europe Network

The paper introduces an analysis of a real inter-organizational innovation network with a network science approach. The study is integrated with a Social Network Analysis referring to the EEN

A new measure for community structures through indirect social connections

Based on an expert systems approach, the issue of community detection can be conceptualized as a clustering model for networks. Building upon this further, community structure can be measured through a clustering coefficient, which is generated from the number of existing triangles around the nodes over the number of triangles that can be hypothetically constructed. This paper provides a new definition of the clustering coefficient for weighted networks under a generalized definition of triangles. Specifically, a novel concept of triangles is introduced, based on the assumption that, should the aggregate weight of two arcs be strong enough, a link between the uncommon nodes can be induced. Beyond the intuitive meaning of such generalized triangles in the social context, we also explore the usefulness of them for gaining insights into the topological structure of the underlying network. Empirical experiments on the standard networks of 500 commercial US airports and on the nervous system of the Caenorhabditis elegans support the theoretical framework and allow a comparison between our proposal and the standard definition of clustering coefficient

Organizing collaboration in inter-organizational innovation networks, from orchestration to choreography

Innovation networks constitute a valid structure within which to foster members' abilities to interact and cooperate, in order to reduce environmental uncertainty and face the challenges that derive from economic change. Network members take advantage of their participation in the system by creating and extracting value when performing certain deliberate and purposeful activities. Traditionally, the interactions between network members are represented in a hierarchical structure with a prominent member performing a leadership role in managing the system. Recently, more complex organizations have emerged in which the power of the decisions is spread among all partners. In this paper, we overcome the single hub model and propose a new organizational framework called "choreography", which takes into account all network members, extending the roles of coordination and management throughout the entire network. We consider a real inter-organizational innovation network as an eligible case study which supports the choreography model

Revealing correlations between structure and innovation attitude in inter-organisational innovation networks

Innovation networks constitute a valid structure in which to foster members’ abilities to interact and cooperate, reducing environmental uncertainty and enhancingways to deal with the challenges that derive from economic change. This paper analyses the correlation between the structure of inter-organisational innovation networks and innovation performance. We consider the correlations between weighted quantities and the underlying structure of the network to describe hierarchies and organisational principles, arguing for their influence on innovation. To attest the effectiveness of the approach we propose, as a case study, the Enterprise Europe Network, describing its architecture along with its quantitative information

Clairvoyant targeted attack on complex networks

Complex networks' resilience against attacks represents a crucial issue in terms of network structure integrity. We investigate the effect of removing nodes on the network diameter in the case of a simultaneous targeted attack and sequential targeted attack. The analysis has been implemented on several network instances, taking into account different centrality measures and clustering coefficients values. Empirical networks have also been observed to compare the effects of the two removal schemes. According to classical literature, we assume that the network attacker has a wide-ranging knowledge of the system. It can be defined as clairvoyant since it knows, a priori, of all the characteristics of the problem's instances. This awareness is not always applicable when real networks are characterised by a dynamic environment. Hence, we distinguish between clairvoyant and non-clairvoyant attacks