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Effect of network topology and node centrality on trading.
Felipe Maciel Cardoso1,2, Carlos Gracia-Lázaro3,4,5, Frederic Moisan6
1Institute for Biocomputation and Physics of Complex Systems, Universidad de Zaragoza, Zaragoza, Spain.
Scientific Reports
|July 8, 2020
Summary
Global supply network efficiency is impacted by network structure. Small-world networks lead to higher prices and less efficient trade compared to random networks, affecting overall economic performance.
Area of Science:
- Economics
- Network Science
- Behavioral Economics
Background:
- Global supply networks are crucial for agriculture, manufacturing, and services.
- Intermediary choices significantly influence network efficiency and surplus distribution.
- Understanding intermediary behavior in complex networks is vital for economic optimization.
Purpose of the Study:
- To investigate how network topology affects price formation and trade efficiency.
- To understand the behavioral principles governing intermediaries in supply networks.
- To model and simulate price dynamics in different network structures.
Main Methods:
- Conducted price formation experiments with human subjects in large, complex networks.
- Compared trade efficiency and pricing in small-world versus random networks.
- Developed and simulated an agent-based model (ABM) based on observed trader behavior.
Main Results:
- Small-world networks exhibited higher prices and significantly lower trade efficiency than random networks.
- Trader location within the network was not a significant factor in pricing outcomes.
- Agent-based model simulations replicated experimental findings on pricing and efficiency.
Conclusions:
- Network topology is a key determinant of pricing and efficiency in global supply networks.
- Small-world network structures inherently lead to less efficient economic outcomes.
- The study provides a foundation for optimizing supply network design through network topology considerations.
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