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      Global Trade Pattern of Traditional Chinese Medicines and China's Trade Position

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          Abstract

          To depict the evolution of the global trade of traditional Chinese medicine (TCM) products, this article analyzes the 2001–2020 trade data of TCM products in the World Bank and United Nations Commodity Trade Statistics Database to discern the spatial-temporal evolution characteristics of global and China's trade patterns of TCM products from 2001 to 2020 and thereby assess the changes in the global trade of TCM products and in the positions of various countries or regions in the global trade of TCM products. Research findings are as follows: First, on the whole, the total trade volume of TCM products and the number of participating economies and trade connections are on the rise. Second, in terms of topological structure, with higher network density and rising transmission efficiency, the global trade network of TCM products has typical small-world and scale-free network characteristics and has begun to be controlled by a few countries. Judging from the co-opetition between major trading countries, there are more diversified sources of imports for major trading countries, and there is competition between supplying countries. Third, For China, the trade volume of TCM products between China and various countries worldwide has grown rapidly and exhibits a trend of continuous increase followed by decline. China has established extensive trade partnerships and its position in the global trade network of TCM products has been continuously improved. China's participation has contributed to a closer connection among trading entities, but its network heterogeneity remains to be further improved. From the perspective of trade interdependence, the number of countries or regions maintaining high interdependence with China has been gradually increasing, and most of them are European and American countries, Japan, and Southeast Asian countries. The number of countries or regions maintaining low interdependence with China has gradually decreased, and countries or regions that are completely one-way dependent on China are nonexistent.

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          Most cited references18

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          Topology of the world trade web

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            Structure and evolution of the global seafood trade network

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              Why social networks are different from other types of networks.

              We argue that social networks differ from most other types of networks, including technological and biological networks, in two important ways. First, they have nontrivial clustering or network transitivity and second, they show positive correlations, also called assortative mixing, between the degrees of adjacent vertices. Social networks are often divided into groups or communities, and it has recently been suggested that this division could account for the observed clustering. We demonstrate that group structure in networks can also account for degree correlations. We show using a simple model that we should expect assortative mixing in such networks whenever there is variation in the sizes of the groups and that the predicted level of assortative mixing compares well with that observed in real-world networks.
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                Author and article information

                Contributors
                Journal
                Front Public Health
                Front Public Health
                Front. Public Health
                Frontiers in Public Health
                Frontiers Media S.A.
                2296-2565
                28 April 2022
                2022
                : 10
                : 865887
                Affiliations
                [1] 1School of Business Administration, Zhejiang University of Finance and Economics , Hangzhou, China
                [2] 2School of Economics and Management, Tongji University , Shanghai, China
                [3] 3Institute of Spatial Planning and Design, Zhejiang University City College , Hangzhou, China
                [4] 4Institute of International Business and Economics Innovation and Governance, Shanghai University of International Business and Economics , Shanghai, China
                Author notes

                Edited by: Xiao-Bing Zhang, Huaiyin Institute of Technology, China

                Reviewed by: Qian Li, Beijing Technology and Business University, China; Li Xin Guo, Huaiyin Institute of Technology, China

                *Correspondence: Haiyan Zhou zhouhaiyansh@ 123456hotmail.com

                This article was submitted to Health Economics, a section of the journal Frontiers in Public Health

                †These authors have contributed equally to this work and share first authorship

                Article
                10.3389/fpubh.2022.865887
                9116222
                35602159
                bcc9aa60-8d1d-4090-b4d6-5ac992b97ccb
                Copyright © 2022 Xiang, Chen, Wei and Zhou.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 30 January 2022
                : 21 March 2022
                Page count
                Figures: 8, Tables: 7, Equations: 0, References: 18, Pages: 15, Words: 8282
                Categories
                Public Health
                Original Research

                trade of traditional chinese medicine products,complex network,topological structure,spatial-temporal pattern,interdependence

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