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Decoding Complexity [electronic resource] : Uncovering Patterns in Economic Networks / by James B. Glattfelder.

By: Contributor(s): Material type: TextTextSeries: Springer Theses, Recognizing Outstanding Ph.D. ResearchPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Description: XVI, 228 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642334245
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 621 23
LOC classification:
  • QC1-QC999
Online resources:
Contents:
The Main Methodology: Computing Control in Ownership Networks -- Backbone of Complex Networks of Corporations: The Flow of Control -- The Network of Global Corporate Control -- The Bow-Tie Model of Ownership Networks.
In: Springer eBooksSummary: Today it appears that we understand more about the universe than about our interconnected socio-economic world. In order to uncover organizational structures and novel features in these systems, we present the first comprehensive complex systems analysis of real-world ownership networks. This effort lies at the interface between the realms of economics and the emerging field loosely referred to as complexity science. The structure of global economic power is reflected in the network of ownership ties of companies and the analysis of such ownership networks has possible implications for market competition and financial stability. Thus this work presents powerful new tools for the study of economic and corporate networks that are only just beginning to attract the attention of scholars.
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The Main Methodology: Computing Control in Ownership Networks -- Backbone of Complex Networks of Corporations: The Flow of Control -- The Network of Global Corporate Control -- The Bow-Tie Model of Ownership Networks.

Today it appears that we understand more about the universe than about our interconnected socio-economic world. In order to uncover organizational structures and novel features in these systems, we present the first comprehensive complex systems analysis of real-world ownership networks. This effort lies at the interface between the realms of economics and the emerging field loosely referred to as complexity science. The structure of global economic power is reflected in the network of ownership ties of companies and the analysis of such ownership networks has possible implications for market competition and financial stability. Thus this work presents powerful new tools for the study of economic and corporate networks that are only just beginning to attract the attention of scholars.

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