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Topological Analysis and Robustness Assessment of the Global Polysilicon Trade Network: Implications for Information Management

Published: 15 October 2024 Publication History

Abstract

Polysilicon, a critical raw material for photovoltaic cell production, plays a vital role in global energy development and technological advancement. This study constructs and analyzes the Global Polysilicon Trade Network (GPSTN) using complex network theory, drawing on trade data from the United Nations Comtrade Database spanning 2000 to 2022. The study examines the network's topological evolution through parameters including density, average clustering coefficient, and heterogeneity index. Additionally, it evaluates network robustness under different node removal scenarios. Results reveal the GPSTN's core-periphery structure, with China and Japan emerging as major importers, while the United States and Germany dominate exports. The network demonstrates strong resilience against random disruptions but exhibits significant vulnerability to targeted removals of key nodes. These findings underscore the importance of enhanced monitoring and risk management strategies for critical nodes in global trade networks. The study provides valuable insights for information management, emphasizing the need for adaptive approaches to improve network stability and resilience in an increasingly complex global trade landscape.

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IMMS '24: Proceedings of the 2024 7th International Conference on Information Management and Management Science
August 2024
465 pages
ISBN:9798400716997
DOI:10.1145/3695652
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 October 2024

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Author Tags

  1. Complex network analysis
  2. Information management
  3. Network robustness
  4. Polysilicon trade network
  5. Trade flow dynamics

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