Network theory

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

Events And Temporality In Business Networks: A Conceptual Analysis

Abstract: Perspectives of temporality in networks in business marketing is analysed in this conceptual paper. Core foundations of business network theory are analysed taking especially time and timing into consideration. A model of event-based networks is developed in grasping the temporal nature of business networks. The findings suggest extensions of network theory, methods and models using events as a promising but complex avenue for research.

Network Theory and Switching Behaviors: A User Guide for Analyzing Electronic Records Databases

Abstract: As part of studies that employ health electronic records databases, this paper advocates the employment of graph theory for investigating drug-switching behaviors. Unlike the shared approach in this field (comparing groups that have switched with control groups), network theory can provide information about actual switching behavior patterns. After a brief and simple introduction to fundamental concepts of network theory, here we present (i) a Python script to obtain an adjacency matrix from a records database and (ii) an illustrative example of the application of network theory basic concepts to investigate drug-switching behaviors. Further potentialities of network theory (weighted matrices and the use of clustering algorithms), along with the generalization of these methods to other kinds of switching behaviors beyond drug switching, are discussed.

Measuring Centrality in Legal Citation Networks – A Case Study of the HITS and PageRank Algorithms

Abstract: The use of network analysis in legal studies has increased rapidly in recent years. Many legal scholars have been attracted to network analysis, among other things by the possibility of conducting large-scale studies of case law. However, when in time we study a citation network impacts the results, sometimes significantly. To reduce this problem, this paper proposes that scholars use PageRank when studying inward citations in legal citation network and a similar measurement, HubRank, when studying outward citations, rather than the HITS algorithm. However, the paper also advocates further methodological discussion and development.

Discovering Influencers for Spreading in Weighted Networks

Abstract: Identifying the influential nodes in networks is an important issue for efficient information diffusion, controlling rumors and diseases and optimal use of network structure. The degree centrality which considers local topology features, does not produce very reliable results. Despite better results of global centrality such as betweenness centrality and closeness centrality, they have high computational complexity. So, we propose semi-local centrality measure to identify influential nodes in weighted networks by considering node degree, edges weight and neighboring nodes. This method runs in O(n(k)2). So, it is feasible for large scale network. The results of applying the proposed method on weighted networks and comparing it with susceptible-infected-recovered model, show that it performs good and the influential nodes are generated by our method can spread information well.

Strategic Network for the Synchronization of Production and Distribution

Abstract: This paper presents an introductory finding in a case study of the convenience store system in Japan. Based upon two theories, strategic network theory and postponement-speculation theory, the evolutionary process of the convenience store system is explained.