Network theory

About: Network theory is a research topic. Over the lifetime, 2257 publications have been published within this topic receiving 109864 citations.

Topological Strata of Weighted Complex Networks.

Abstract: The statistical mechanical approach to complex networks is the dominant paradigm in describing natural and societal complex systems. The study of network properties, and their implications on dynamical processes, mostly focus on locally defined quantities of nodes and edges, such as node degrees, edge weights and –more recently– correlations between neighboring nodes. However, statistical methods quickly become cumbersome when dealing with many-body properties and do not capture the precise mesoscopic structure of complex networks. Here we introduce a novel method, based on persistent homology, to detect particular non-local structures, akin to weighted holes within the link-weight network fabric, which are invisible to existing methods. Their properties divide weighted networks in two broad classes: one is characterized by small hierarchically nested holes, while the second displays larger and longer living inhomogeneities. These classes cannot be reduced to known local or quasilocal network properties, because of the intrinsic non-locality of homological properties, and thus yield a new classification built on high order coordination patterns. Our results show that topology can provide novel insights relevant for many-body interactions in social and spatial networks. Moreover, this new method creates the first bridge between network theory and algebraic topology, which will allow to import the toolset of algebraic methods to complex systems.

Networks, Societies, Spheres: Reflections of an Actor-Network Theorist

Abstract: Keynote speech for the Second International Seminar On Network Theory: Network Multidimensionality In The Digital Age.

Shaping Sustainable Value Chains: Network Determinants of Supply Chain Governance Models

Abstract: Although the characteristics and advantages of interorganizational governance models based on extensive collaboration are well established in the literature, inquiry has only recently extended to sustainable supply chain management, highlighting the potential benefits of combining the integration of social and environmental issues concerning the supply chain with governance models based on joint decision making and extensive cooperation. Yet, firms still differ in both the pervasiveness of such collaborative approaches along the value chain and the extent to which sustainability issues are addressed to the advantage of all parties involved. In an attempt to predict variety in the governance models related to sustainability along the value chain, we propose a theoretical model that identifies and frames four sustain- able supply chain governance (SSCG) models, resulting from combinations of supply chain network density and centrality of the focal organizations. We show how, as centrality increases, firms are able to exert influence over their network, coordinating integrated approaches along the value chain. Moreover, as high centrality combines with increasing interconnectedness of the actors within a supply chain network, instrumental approaches are progressively replaced by more relational attitudes aimed at joint value creation among partners. Conditions for SSCG models’ success and the main benefits gained by firms in different structural contexts are also discussed.

Queueing networks- customers, signals, and product form solutions

Abstract: considerations. Most of these open problems are easily stated and put into a theoretical framework, but they often require either intricate techniques on an ad hoc basis or deep mathematical methods. Often, both of these approaches have to be combined to tackle successfully the solution of quickly formulated problem. The development of queueing network theory, which provided application areas with solutions, formulas, and algorithms, commenced around 1950 in the area of Operations Research, with special emphasis on production, inventory, and transportation. The first breakthroughs were the works of Jackson [10] and Gordon and Newell [10]; both papers appeared in Operations Research. The second breakthrough in queueing network theory was already connected with Computer Science: the celebrated papers of Baskett, Chandy, Muntz, and Palacios [2], which appeared in the Journal of the Association for Computing Machinery, and of Kelly [11]. The two volumes of Kleinrock’s book [13, 14] appeared at the same time as [11]. From that time on, queueing network theory and its applications have become intimately connected with performance analysis of complex systems in Computer and Communication Sciences, both at the hardware and software levels. Today’s growth of production, manufacturing, and transportation, with information processing and communi