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Network theory

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


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Journal ArticleDOI
TL;DR: This work develops an approach that allows the analysis of movement data using network theory by defining occupied pixels as nodes and connection among these pixels as edges, providing a framework for conservationists to analyze movement data.
Abstract: Network (graph) theory is a popular analytical framework to characterize the structure and dynamics among discrete objects and is particularly effective at identifying critical hubs and patterns of connectivity. The identification of such attributes is a fundamental objective of animal movement research, yet network theory has rarely been applied directly to animal relocation data. We develop an approach that allows the analysis of movement data using network theory by defining occupied pixels as nodes and connection among these pixels as edges. We first quantify node-level (local) metrics and graph-level (system) metrics on simulated movement trajectories to assess the ability of these metrics to pull out known properties in movement paths. We then apply our framework to empirical data from African elephants (Loxodonta africana), giant Galapagos tortoises (Chelonoidis spp.), and mule deer (Odocoileous hemionus). Our results indicate that certain node-level metrics, namely degree, weight, and betweenness, perform well in capturing local patterns of space use, such as the definition of core areas and paths used for inter-patch movement. These metrics were generally applicable across data sets, indicating their robustness to assumptions structuring analysis or strategies of movement. Other metrics capture local patterns effectively, but were sensitive to specified graph properties, indicating case specific applications. Our analysis indicates that graph-level metrics are unlikely to outperform other approaches for the categorization of general movement strategies (central place foraging, migration, nomadism). By identifying critical nodes, our approach provides a robust quantitative framework to identify local properties of space use that can be used to evaluate the effect of the loss of specific nodes on range wide connectivity. Our network approach is intuitive, and can be implemented across imperfectly sampled or large-scale data sets efficiently, providing a framework for conservationists to analyze movement data. Functions created for the analyses are available within the R package moveNT.

29 citations

Journal ArticleDOI
TL;DR: In this article, the authors leverage economic theory, network theory, and social network analytical techniques to bring greater conceptual and methodological rigor to understand how information is exchanged during disaster, and leverage economic theories and network theories to predict future economic performance.
Abstract: We leverage economic theory, network theory, and social network analytical techniques to bring greater conceptual and methodological rigor to understand how information is exchanged during disaster...

29 citations

Journal ArticleDOI
TL;DR: In this article, the authors synthesize streams of thought on network theory and propose a network perspective of competitive advantage, which is based on the structural characteristics of the network in which the firm is embedded and its position in the same.
Abstract: This article synthesizes streams of thought on network theory and proposes a network perspective of competitive advantage. Competitive advantage arises from the structural characteristics of the network in which the firm is embedded and its position in the same. Using concepts from network theory, the study develops a model that shows how the structural characteristics—connectedness, weak ties, structural holes and network centrality—lead to benefits such as adaptation, knowledge, control, and resources, which in turn lead to competitive advantage.

29 citations

Journal ArticleDOI
TL;DR: It is shown that topological–angular centrality measures correlate better than does the metric centrality measure with the aggregate flows of agents who choose the shortest angular, topological or metric routes.

29 citations

Journal ArticleDOI
TL;DR: In this paper, the authors use the idea innovation network theory as a framework for assessing sectoral innovation patterns and identify six types, or "arenas, of research that are linked to innovation within these networks.
Abstract: In this paper, we argue that a new policy model for science and technology is needed and must be evolutionary in nature. The paper proposes utilizing the idea innovation network theory as a framework for assessing sectoral innovation patterns and identifies six types, or “arenas,” of research that are linked to innovation within these networks. Following the idea innovation network theory, the paper argues that two societal trends, the fragmentation of markets and the growth of knowledge, are driving organizations toward greater functional differentiation. Successful innovation will occur when these differentiated organizations become closely linked within innovation networks that integrate the arenas of research. The paper argues that this framework has predictive power, in that it allows the identification of path-dependent blockages or gaps within idea innovation chains that prevent the emergence of effective innovation networks in different countries. Policy makers can play an important role by fostering the development of tightly coupled networks that include organizations involved in each of the types of research. The paper provides empirical support for the framework using a cross-national European study of the telecommunications and pharmaceutical industries.

29 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202319
202240
202175
2020109
201989
2018115