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Mapping the structural evolution in the global scrap copper trade network

Abstract The rise in industrialization and urbanization has elevated consumer lifestyles and has dramatically increased copper consumption in the past three decades. Due to the growing scarcity of copper ore and lower manufacturing costs associated with using recycled copper, copper recycling has gained increasing attention. Because of the uneven geographical distribution of scrap copper, the international scrap copper trade has formed and is experiencing rapid growth. This study applies complex network theory to map the structural evolution of the global scrap copper trade from 1988 to 2017 according to the UN-Comtrade database. The results show that the global scrap copper trade has been reshaped from the pre-existing geopolitical realities through the interaction of geopolitical relations and geo-economics. The America-Asia community is the largest trading community and is driven by the USA and China. China is the largest recipient of scrap copper due to a lack of self-sufficiency with respect to copper and scrap copper resources. India is considered another long-term potential market for exporters, which can result in reducing dependence on a single market such as China. These findings, together with policy-related discussions, help authorities understand the complex international scrap copper trade relationships and propose effective import-export policies to reduce the risk of trade disruption.
- China Medical University Hospital Taiwan
- Beijing University of Technology China (People's Republic of)
- Beijing University of Technology China (People's Republic of)
- Asian University Taiwan
- Asian University Taiwan
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).58 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
