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- W4366607739 endingPage "103542" @default.
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- W4366607739 abstract "As an important non-metallic strategic mineral resource, boron plays an important role in the development of national emerging strategic industries. In this study, a complex network approach, core-periphery model and link prediction model are used to analyze the evolution of international trade and potential future competition of boron ore. The study found that: (1) the international demand and trade volume of boron ore showed a growing trend yearly, with increasingly closer trade relations and higher trade efficiency. (2) Boron ore exports are closely related to resource endowment. Turkey, as the world's largest country in terms of reserves and production, holds the absolute export initiative in the boron ore international trade. Boron ore imports are mainly affected by the level of economic development, China and the United States belong to the control trade importers; European countries are important transit countries. (3) The import competition of boron ore international trade is becoming more and more intense and concentrated, mainly forming a competitive relationship with Turkey as the common import source. And at present, it is mostly a game between economically developed countries, the core of which is the competition of “China-US-India-Europe”; other import competitions are influenced by geographical location. (4) In the future, the potential import competition will gradually develop in emerging economies, and the competition center will gradually move from Europe and Asia to Latin America and Africa. Countries with geographical advantages such as coastal, ports and proximity to boron ore areas will have a greater degree of trade options and competitive development potential." @default.
- W4366607739 created "2023-04-23" @default.
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- W4366607739 date "2023-05-01" @default.
- W4366607739 modified "2023-10-13" @default.
- W4366607739 title "International trade evolution and competition prediction of boron ore: Based on complex network and link prediction" @default.
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- W4366607739 doi "https://doi.org/10.1016/j.resourpol.2023.103542" @default.
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