Network theory

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

Beyond centrality: classifying topological significance using backup efficiency and alternative paths

Abstract: In networks characterized by broad degree distribution, such as the Internet AS graph, node significance is often associated with its degree or with centrality metrics which relate to its reachability and shortest paths passing through it. Such measures do not consider availability of efficient backup of the node and thus often fail to capture its contribution to the functionality and resilience of the network operation. In this paper we suggest the Quality of Backup (QoB) and Alternative Path Centrality (APC) measures as complementary methods which enable analysis of node significance in a manner which considers backup. We examine the theoretical significance of these measures and use them to classify nodes in the Internet AS graph while applying the BGP valley-free routing restrictions. We show that both node degree and node centrality are not necessarily evidence of its significance. In particular, some medium degree nodes with medium centrality measure prove to be crucial for efficient routing in the Internet AS graph.

Some remarks on a social network approach to identifying key sectors

Abstract: Ostensibly, certain adaptations of social network theory extend and improve the traditional key-sector approaches. Our analysis of the underlying algebraic properties shows that a social-network-based approach proposed by Garcia Muniz et al. [(2008) Key Sectors: A New Proposal from Network Theory. Regional Studies, 42, 1013–1030] does not relate final demand and output in ways comparable to key-sector measures that are based on the static Leontief input–output model. Using the most recent IO table for Poland we show that the modified approach can lead to spurious empirical results and, as a consequence, to false policy implications.

Strong Ties within Cultural Organization Event Networks and Local Development in a Tale of Three Festivals

Abstract: The purpose of this article is to provide a deeper understanding of successful event networks and offer a conceptual framework which can be used to analyze their impact on local development. We address two research questions. First, how does network structure affect the success of the event and its outcomes on local development, other than in economic terms? Second, which main capabilities does the "network orchestrator" need in order to promote the effectiveness of the event network? By analyzing three different Italian cultural festivals this article sheds light on: (a) the features of successful event networks, (b) the dynamics linking network structure and the social outcomes generated, and (c) the typical bundle of relational capabilities that network orchestrators need. In particular, two different archetypes of event networks - namely, "Community-driven events" versus "Market-driven events" - emerge, which are related to different outcomes on local development.We draw some implications for management and offer some remarks to stimulate further research in the field of special events.

Combining network theory with corporate governance: converging models for connected stakeholders

Abstract: JEL Classification: G32, K22, M13, M21, O31 DOI: 10.22495/cocv17i1art12 Traditional corporate governance patterns are based on the interaction among composite stakeholders and the various forms of separation between ownership and control. Stakeholders cooperate around the Coasian firm represented by a nexus of increasingly complex contracts. These well-known occurrences have been deeply investigated by growing literature and nurtured by composite empirical evidence. Apparently, unrelated network theory is concerned with the study of graphs as a representation of (a)symmetric relations between discrete objects (nodes connected by links). Network theory is highly interdisciplinary, and its versatile nature is fully consistent with the complex interactions of (networked) stakeholders, even in terms of gametheoretic patterns. The connection between traditional corporate governance issues and network theory properties is, however, still under-investigated. Hence the importance of an innovative reinterpretation that brings to “network governance”. Innovation may, for instance, concern the principal-agent networked relationships and their conflicts of interest or the risk contagion and value drivers – three core governance issues. Networks and their applications (like blockchains, P2P platforms, game-theoretic interactions or digital supply chains) foster unmediated decentralization. In decentralized digital platforms stakeholders inclusively interact, promoting cooperation and sustainability. To the extent that network properties can be mathematically measured, governance issues may be quantified and traced with recursive patterns of expected occurrences.

Effects of self-organization on transport in granular matter: A network-based approach

Abstract: Granular matter may be one of the simplest prototypes of what have come to be regarded as complex systems —systems where simple interactions can lead to rich, often surprising, global behavior. For example, interparticle contacts in a granular system give rise to networks that are 1) heterogeneous, i.e., a few particles support high compressive force, while many others support relatively little, and 2) self-organized, i.e., spatially correlated strong forces tend to form a sub-network of interconnecting "force chains". Using numerical simulations, we investigate the influence of heterogeneity and self-organization on the transport properties of granular matter, with particular attention to heat conduction —a phenomenon of ubiquitous importance in engineering and nature. We find that self-organization in the granular network promotes efficient transport. Furthermore, a network-attack experiment suggests that contacts with high betweenness centrality, not necessarily those with highest local heat transfer coefficient, most significantly influence transport behavior. We find that concepts of network theory yield valuable insight —both qualitative and quantitative— into the observed behavior.