Network theory

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

From static to temporal network theory - applications to functional brain connectivity

Abstract: Network neuroscience has become an established paradigm to tackle questions related to the functional and structural connectome of the brain. Recently, there has been a growing interest to examine the temporal dynamics of the brain's network activity. While different approaches to capture fluctuations in brain connectivity have been proposed, there have been few attempts to quantify these fluctuations using temporal network theory. Temporal network theory is an extension of network theory that has been successfully applied to the modeling of dynamic processes in economics, social sciences and engineering. The objective of this paper is twofold: (i) to present a detailed description of the central tenets and outline measures from temporal network theory; (ii) apply these measures to a resting-state fMRI dataset to illustrate their utility. Further, we discuss the interpretation of temporal network theory in the context of the dynamic functional brain connectome. All the temporal network measures and plotting functions described in this paper are freely available as a python package Teneto.

Overcoming African institutional voids: market entry with networks

Abstract: Literature on modes of entry has focussed on firm-level strategies. The predominant theories used are institutional theory and the resource-based view. Using an alternate approach – network theory – this paper aims to demonstrate an additional mode of entry: multiple firms entering together as an extension of an existing loose network, known as a bridging network. The extension of an external network across borders is an appropriate mode of entry in emerging markets, with no pre-existing networks or existing networks within a market that are weak, immature or missing.,A conceptual review, which develops four propositions, demonstrating that market entry with bridging networks may be the preferred mode of entry in the presence of institutional voids. Alternative modes may not be viable because of costs and risks associated with overcoming such voids.,Existing theory and case examples support the contention that market conditions facilitate firms to enter as networks rather than as singular entities. These conditions are found in markets with institutional voids and explain the dominant form of business groups in many countries and the operation of loose strategic alliances in emerging markets. Network entry facilitates market access speed may allow for local ties to remain undeveloped or be a first step in building in-country networks.,This paper heeds to the call for a network ecosystem approach to market entry, arguing that firms may enter as a collective in subsistence and emerging markets, which would explain the preponderance of business groups and loose alliances found.

Understanding structure and behavior of systems: a network perspective

Abstract: Networks are interesting representation models for analysis of systems. The entities of the systems under review can be denoted as the nodes of the networks and the relationships between these entities as the edges connecting them. Such a representation has advantages in analysis as network theory has a rich collection of well defined concepts and methods. These concepts of can be applied on such networks to draw inferences about the systems. As digitization has penetrated almost all aspects of mankind, a wide variety of systems from diverse domains such as computer science, transportation, social science have become available in the form of networks. A network perspective provides valuable insights into their structure and behavior. In this inquiry networks representing real world systems from different domains are analyzed using concepts of network theory and statistical generative network models—SBM and LSM. This is done to various application scenarios to express the properties of these systems. The findings highlight the unique features and trends seen in each domain.

Formal versus self-organised knowledge systems: A network approach

Abstract: In this work, we consider the topological analysis of symbolic formal systems in the framework of network theory. In particular, we analyse the network extracted by Principia Mathematica of B. Russell and A.N. Whitehead, where the vertices are the statements and two statements are connected with a directed link if one statement is used to demonstrate the other one. We compare the obtained network with other directed acyclic graphs, such as a scientific citation network and a stochastic model. We also introduce a novel topological ordering for directed acyclic graphs and we discuss its properties with respect to the classical one. The main result is the observation that formal systems of knowledge topologically behave similarly to self-organised systems.