Affiliation:
1. Department of Computer Science and Telecommunication Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh
2. Department of Physics, Inha University, Incheon 22212, Republic of Korea
Abstract
We explore the evolution of modular structure within the International Trade Network (ITN) for eight commodities, employing the Louvain module optimization method. The interactions among countries in the realm of trade are shaped by various factors, including economic conditions and geographical proximity. These countries are often categorized into continental groups, a classification that frequently persists even after the detecting process of modules. Nonetheless, African countries display a penchant for shifting among different modules over time. Observations of module trends unveil the increase in regional trade up until 2005, followed by plateaus marked with interruptions during significant crises, such as the 2012–2014 EU recession and the 2018 trade war. Notably, the 2018 trade war witnessed a sharp upsurge in module, attributed to robust alliances between major players like China and the USA. These modular dynamics are not uniform across different commodities; they exhibit varying degrees of module and distinct responses during times of crisis, with human-made goods displaying heightened sensitivity. Core nations, such as the USA, Germany, China, and Japan, exert significant influence over the commodities and often demonstrate a cohesive approach when navigating through crises. The analysis of modular dynamics provides valuable insights into global trade trends, fostering sustainability in trade practices, and comprehending the impacts of crises on various commodities.
Funder
Ministry of Education of the Republic of Korea and the National Research Foundation of Korea
Bangladesh and the ministry of ICT of Bangladesh
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
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