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Asymmetric disassembly and robustness in declining networks.

Serguei Saavedra¹, Felix Reed-Tsochas, Brian Uzzi

¹Department of Engineering Science and CABDyN Complexity Centre, Oxford University, Oxford OX1 3PJ, United Kingdom.

Proceedings of the National Academy of Sciences of the United States of America

|October 22, 2008

Summary

Declining networks can maintain structure and function by favoring asymmetric links during contraction. This strategy helps preserve network integrity even with significant node loss, unlike simple reverse growth processes.

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Area of Science:

Network Science
Sociology
Economics

Background:

Understanding how networks maintain structure during decline is crucial but poorly understood.
Existing models predominantly focus on network growth, neglecting decline dynamics.
Data on declining networks is scarce, limiting research in this area.

Purpose of the Study:

To investigate the mechanisms that allow declining networks to avoid structural collapse and performance degradation.
To analyze the evolution of network topology and global performance during decline.
To develop and test a model explaining network robustness under contraction.

Main Methods:

Analysis of over 700,000 firm transactions in the New York garment industry over 19 years.
Tracking network decline, topology, and global performance evolution.
Developing and simulating a network decline model combining asymmetric disassembly and preferential attachment.

Main Results:

Favoring asymmetric (disassortative) links is critical for preserving the topology and functionality of declining networks.
The proposed model successfully explains network robustness during decline, even with over an order of magnitude contraction in nodes.
Disassembly processes in network decline are distinct from simple reverse assembly mechanisms.

Conclusions:

Asymmetric link formation is a key strategy for network resilience during decline.
The developed model provides insights into network collapse and robustness across various domains.
Findings challenge the notion that network decline is merely the inverse of network growth.