<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">AJIBM</journal-id><journal-title-group><journal-title>American Journal of Industrial and Business Management</journal-title></journal-title-group><issn pub-type="epub">2164-5167</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ajibm.2021.1111065</article-id><article-id pub-id-type="publisher-id">AJIBM-112969</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Business&amp;Economics</subject></subj-group></article-categories><title-group><article-title>
 
 
  Research on the Structural Characteristics and Evolution of the Asia-Pacific Trade Network of the ICT Industry&lt;br/&gt;—From the Perspective of Global Value Chain
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Yanxi</surname><given-names>Huang</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Qiming</surname><given-names>Tang</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>School of Economics, Wuhan University of Technology, Wuhan, China</addr-line></aff><pub-date pub-type="epub"><day>03</day><month>11</month><year>2021</year></pub-date><volume>11</volume><issue>11</issue><fpage>1071</fpage><lpage>1088</lpage><history><date date-type="received"><day>4,</day>	<month>October</month>	<year>2021</year></date><date date-type="rev-recd"><day>1,</day>	<month>November</month>	<year>2021</year>	</date><date date-type="accepted"><day>4,</day>	<month>November</month>	<year>2021</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  The ICT industry has gradually become an important industry in the regional economy. The global traditional, simple and complex value chain trade netw
  ork
   has undergone fundamental changes during the evolution proce
  ss, which has changed the overall pattern of the global value chain trade network. This a
  rticle uses the UIBE GVC Indicators database, based on the global value
   chain theory to construct a trade network for the ICT industry in the Asia-Pacific region by the means of social network analysis methods. It uses the visualizat
  ion software Gephi to analyze the evolution characteristics of th
  e Asia-Pacific trade network in the ICT industry from 2005 to 2015. The analysis results found that: the total volume of the trade network continued to improve steadily, the location of the regional center of the trade network has changed. The steady network has help
  ed
   the recovery of the trade after the external shocks. Also, China has played a more significant role in the ICT industry’s network from the perspective of global value chain.
 
</p></abstract><kwd-group><kwd>ICT Industry</kwd><kwd> Trade Network Evolution Characteristics</kwd><kwd> Global Value Chain</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>The ICT industry is a new technology field formed by the integration of the information technology (IT) and communication technology (CT) industries, with branches in the manufacturing and service industries. The ICT industry is a strategic industry that builds a national information infrastructure and supports economic and social development. Countries around the world focus on strengthening support for the development of the ICT industry. During the “12th Five-Year Plan” period, China listed the ICT industry as one of the seven strategic new industries, which promoted the rapid development of the ICT industry. Especially after entering the “14th Five-Year Plan”, China’s ICT industry has transformed from large-scale development to high-quality development and plays an important role in Asia and the world.</p><p>With the development of global value chains, the degree of regionalization of trade has increased day by day, and important changes have taken place in the characteristics and structure of the international division of labor in ICT. The rapid rise of China’s ICT industry has greatly changed the overall pattern of the industry’s global value chain trade network, especially in the Asia-Pacific region. From the perspective of the global production network topology, China has gradually become an important supply and demand center in traditional trade and global value chain production, while the United States and Germany are still the most important hubs in the complex global value chain network.</p><p>This article uses social network analysis methods, based on the global value chain theory and international division of labor theory, and the value-added data of the UIBE GVC Indicator database from 2005 to 2015, to construct an ICT industry trade network in the Asia-Pacific region, and analyzes the changes in the total import and export volume of traditional trade, simple and complex value chains, the evolution of the trade network structure, and the changes in the weighted out degree and weighted in degree of the trade network. It provides a new perspective for the development and evolution of trade networks. At the same time, this article explains that further deepening participation in the global value chain and maintaining the stability of the value chain system will help China improve its position in the global value chain system against the background of the COVID-19 and trade protectionism.</p></sec><sec id="s2"><title>2. Literature Review</title><p>The social network analysis method has been widely used in the field of international trade. It describes the social structure and characteristics of group relations through points and lines. At present, the research on the temporal and spatial pattern evolution, topological structure and influencing factors of the global trade network mainly starts from the overall pattern. Chen Yinfei (2011), Zhang Qin et al. (2012) build a global trade network based on the total trade value and study the evolution of its network structure; Cheng Shujia and Wang Zhaojun (2011), Sun Xiaolei et al. (2012), Liu Jian (2013), Liu Jinsong (2016), Wang Xiang et al. (2018) conducted research based on specific manufacturing or service industry sectors, such as characterizing the evolution of global trade networks of commodity industries such as oil and natural gas.</p><p>From the perspective of total value trade, there have been numerous literatures systematically discussed. Chen Yinfei (2011) used total value of import and export data to represent bilateral trade volume between countries, and constructed a total value trade network. Through network characteristic indicators such as density and centrality, as well as core-periphery analysis, he found that while the Internet status of the United States continues to decline before and after the subprime mortgage crisis, the network status of Japan, Germany, Britain, France, and the BRIC countries have all increased significantly (Zhang &amp; Li, 2012). Through the establishment of a total value trade network of the top 50 international trades from 2001 to 2010, network characteristic indicators, “core-periphery” analysis and structural hole analysis, he found that although our country’s position in the trade network continues to increase, there is still a gap between China and the United States, Germany and other countries, and China needs to further enhance the right to speak and influence. Yang Wenlong et al. (2018) constructed a total value trade network of countries along the “Belt and Road”. Through the gravity model and QAP analysis, they found that the network has a small-world nature. The spatial structure of the network shows the characteristics of “hybrid” network structure with China as the core and Russia, ASEAN and UAE as the secondary core. There are also some studies that divide the global trade network into different regional trade networks based on the construction of a global trade network, and analyze and compare the structural differences between the global network and the regional network (Xu et al., 2015</p><p>Therefore, based on the UIBE GVC Indicator database, this article uses the WWZ accounting method to calculate the trade value, and uses the social network analysis method to construct the Asia-Pacific ICT industry trade network structure and evolution process.</p></sec><sec id="s3"><title>3. Construction of the Asia-Pacific Trade Network for the ICT Industry</title><sec id="s3_1"><title>3.1. Network Construction Method</title><p>This article mainly constructs a collection of trade network relationships among 17 countries and regions in the ICT industry in the Asia-Pacific region. According to the description method of the complex network, the vector V i = [ v i ] ( i = 1 , 2 , ⋯ , n ) represents the exporting country, the vector V j = [ v j ] ( j = 1 , 2 , ⋯ , n ) represents the importing country, and the weight matrix W = [ W i , j ] ( i = 1 , 2 , ⋯ , n ; j = 1 , 2 , ⋯ , n ) represents the domestic value added of trade between the two countries. In the weight matrix W, the weighted out-degree W i out and the weighted in-degree W i in are the domestic added value of exports from country V i to country V j and from country V j to country V i . V i , V j and W together form the Asia-Pacific trade network of the ICT industry, denoted as G = ( V i , V j , W ) .</p><p>In order to further compare the differences of the Asia-Pacific trade network of the ICT industry from the perspective of global value chain and total value trade, this paper constructs a regional trade network in the three dimensions of traditional trade, simple value chain trade and complex value chain trade from 2005 to 2015. It also uses Gephi software to visualize the three-dimensional trade network and draw the topological map of the trade network. Furthermore, this article studies the evolution and structural characteristics of the Asia-Pacific trade network of the ICT industry by combining the weighted out-degree and weighted in-degree change trends of various countries (regions).</p></sec><sec id="s3_2"><title>3.2. Data Sources</title><p>Shen Haoran (2019) believes that the ISIC classification only includes the ICT service industry in the ICT industry, and is not enough to represent the development of the entire ICT industry. The OECD classification not only includes the ICT service industry, but also includes the ICT industry manufacturing industry, and the data is more comprehensive. Therefore, according to the definition of the ICT industry in the OECD database, which reflects data on the number of countries or regions, the number of industrial sectors included, the time span, and processing trade. this article screened the D26, D61, D62T63 classification data in the OECD-ICIO 2018 sub-table to represent the entire ICT industry. Among them, the meaning of each classification is shown in <xref ref-type="table" rid="table1">Table 1</xref>.</p><p>The UIBE GVC Indicators is a non-profit database for academic research, which provides trade in value added indicators and global value chain (GVC) related indicators. It is a secondary database, which is processed based on the public released ICIO tables. This article uses the UIBE GVC Indicators database, which is processed based on the public released OECD-ICIO2018 tables, and the WWZ algorithm proposed by Wang et al. (2013) and Wang Zhi et al. (2015). Based on the input-output perspective, further decomposition of total trade exports is achieved by diverting intermediate goods trade, and finally the decomposition of one country’s exports to another country is expressed as:</p><p>T E X = D V A F I N + D V A I N T + D V A I N T R E X ︸ D V A + M V A + O V A ︸ F V A + D D V + F D C ︸ P D C + R D V (1)</p><p>Among them, DVA<sub>FIN</sub> represents the domestic value-added of a country’s final</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Definition of ICT industry</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >ICT industry classification</th><th align="center" valign="middle" >OECD-ICIO 2018 number</th><th align="center" valign="middle" >Subdivided industries</th></tr></thead><tr><td align="center" valign="middle" >ICT industry manufacturing</td><td align="center" valign="middle" >D26</td><td align="center" valign="middle" >Computer, electronic and optical products</td></tr><tr><td align="center" valign="middle"  rowspan="2"  >ICT service industry</td><td align="center" valign="middle" >D61</td><td align="center" valign="middle" >Telecommunications</td></tr><tr><td align="center" valign="middle" >D62T63</td><td align="center" valign="middle" >IT and other information services</td></tr></tbody></table></table-wrap><p>export products, DVA<sub>INT</sub> represents the domestic value-added of intermediate products absorbed by the direct importing country, DVA<sub>INTREX</sub> represents the domestic added value of intermediate products produced by the direct importing country and exported to a third country and absorbed by a third country. These three parts constitute the domestic value-added DVA absorbed by foreign countries; MVA represents the value-added implied by the importing country in exports, and OVA represents the third-country value-added implied by the exports. These two parts constitute the foreign value-added FVA; RDV represents the domestic value-added returned and absorbed by the country. In addition, the export composition also includes the pure double counting DDC of the domestic account and the pure double counting FDC of the foreign account. These two parts constitute the pure double counting part of the PDC.</p><p>In addition, Wang et al. (2017) divided production activities into four categories based on whether the production process involves the participation of two or more countries, and the three types of production activities involving international trade can be represented by DVA in formula (1).</p><p>According to the meaning of the above DVA sub-items, it can be found that DVA<sub>FIN</sub> represents traditional international trade, DVA<sub>INT</sub> represents simple global value chain trade, and DVA<sub>INTREX</sub> represents complex global value chain trade. Based on this, this paper constructs a three-dimensional domestic value-added regional trade network of traditional trade, simple value chain trade, and complex value chain trade, and conducts research on the evolution of ICT industry trade networks in 17 countries or regions in the Asia-Pacific region from 2005 to 2015.</p></sec><sec id="s3_3"><title>3.3. Construction of Nodes and Edges</title><p>1) Construction of nodes</p><p>This article will take each country or region as a vertex in the trade network, and construct the node of the trade network with 17 countries and regions in the Pacific Rim and Southeast Asia. The size of the node represents the total bilateral domestic value added and represents the position of the country (region) in the Asia-Pacific trade network. The calculation formula for the size of node i is:</p><p>DVA FIN i = ∑ j n DVA FIN out + DVA FIN in (2)</p><p>DVA INT i = ∑ j n DVA INT out + DVA INT in (3)</p><p>DVA INTrex i = ∑ j n DVA INTrex out + DVA INTrex in (4)</p><p>Among them, Equations (2) (3) (4) respectively calculate the node size in the three dimensions of traditional trade, simple value chain trade and complex value chain trade; D V A F I N o u t , D V A I N T o u t , D V A I N T r e x o u t represents the domestic value-added of exports from countryi (region) to country (region); D V A F I N i n , D V A I N T i n , D V A I N T r e x i n represent country (region) j to i. The domestic value-added of exports from countries (regions).</p><p>2) Construction of edge</p><p>In this paper, the domestic value added of each country (region) is used as the weight of the edge, and the trade volume between the nodes in the trade network is used as the edge, and the nodes in the trade network are connected. The thickness of the edge indicates the closeness of trade ties between the countries (regions) at both ends of the connection, and the number of edges indicates the number of trading partners in each country (region). In this article, 17 countries (regions) all have bilateral trade, so this article will take the thickness of edges as the main indicator to analyze the status changes of each country (region) in the process of network evolution. The thickness of the edge is calculated from the sum of the weighted out-degree and the weighted in-degree of each country (region). The calculation formula for the thickness of the edge connecting node i and node j is:</p><p>W i , j = W i out + W i in (5)</p><p>In this formula, W i out represents the weighted outdegree, and W i in represents the weighted indegree.</p></sec></sec><sec id="s4"><title>4. Characteristics and Evolution Trends of the Asia-Pacific Trade Network of the ICT Industry</title><sec id="s4_1"><title>4.1. Characteristics of the Total Import and Export Volume of the Asia-Pacific Trade Network of the ICT Industry</title><p>1) Characteristics of the total import and export volume of traditional trade</p><p>The total volume of the traditional Asia-Pacific trade network of the ICT industry features steady and continuous improvement, relatively stable development, and relatively close trade ties within the region. The total volume of imports and exports of traditional trade has regional characteristics, which can be seen in three levels: core, sub-periphery, and marginal (<xref ref-type="fig" rid="fig1">Figure 1</xref>). China and the United States are at the core of the traditional total trade volume; Canada, Japan, South Korea, India and Taiwan area, PRC<sup>1</sup> are in the sub-peripheral area of the traditional total trade volume; while Russia and other ten countries and regions are at the</p><p>edge of the total traditional trade volume.</p><p>2) Characteristics of total import and export volume of simple and complex value chain trade</p><p>The trend of changes in the total import and export volume of simple and complex value chains is basically stable. The characteristics of increased network closeness are consistent with traditional trade perspectives, and both have an obvious “core-sub-periphery-periphery” structure. However, comparing traditional trade, simple value chain and complex value chain, the following differences can be found: first, China has grown more than other countries (regions) in the Asia-Pacific region in simple and complex value chain trade, and has always maintained the number one position. Therefore, the network importance of China’s ICT industry is underestimated by traditional estimation methods. As shown in <xref ref-type="fig" rid="fig2">Figure 2</xref>, through the development of trade in intermediate goods, China’s simple value chain import and export trade has seen a relatively large increase. In 2011, China’s simple value chain trade volume exceeded that of the United States, and it has gradually become the regional trade center of the ICT industry in the Asia-Pacific region. Second, the importance of key nodes from the perspective of the value chain is slightly different. The core countries (regions) of the simple value chain trade network are still China and the United States, but in the complex value chain trade network, China is even more at the core. Japan is at the secondary edge of the simple value chain network, but its importance in the complex network has diminished. Third, the complex value chain has observed the impact of the 2008 financial crisis on the ICT industry and the recovery process. As shown in <xref ref-type="fig" rid="fig3">Figure 3</xref>, one year after the crisis broke out, trade has basically recovered. During this period, China has taken active countermeasures, increased currency injection to stimulate the economy, and restored the total volume of value chain trade imports and exports to a steady growth.</p></sec><sec id="s4_2"><title>4.2. Analysis of the Characteristics of the Asia-Pacific Trade Network of the ICT Industry</title><p>In the Asia-Pacific trade network of the ICT industry, the status and importance</p><p>of a country (region) can be measured by the network weighting degree. This article uses weighted in-degree and weighted-out degree to discuss the status of different countries (regions) in the Asia-Pacific trade network of the ICT industry. Among them, the weighted in-degree is the measurement of the total domestic value-added imported by the country (region) by other trading partners in the network, and the weighted-out degree is the total domestic value-added exported by the country (region) to other trading partners in the network. Take a measurement. <xref ref-type="table" rid="table2">Table 2</xref> shows the top 10 countries (regions) with weighted in-degrees and weighted-out degrees in traditional trade networks, simple value chain networks, and complex value chain networks in the Asia-Pacific region of the ICT industry in 2000, 2009, and 2015, and their corresponding domestic value added.</p><p>From the perspective of the traditional trade network, the United States has always ranked first in terms of weighted output, and the domestic value-added contained in its traditional trade network is the highest, which is basically in line with its position in the ICT industry. The three countries of China, Japan and India have more obvious changes, and most of the other countries (regions) have basically maintained their weighted out-of-degree rankings. With the continuous rapid development of China’s economy, increased investment in R&amp;D, and the signing of the ITA2.0 (expansion) under the WTO framework has made the traditional trade network rank 7th, reaching the level of US $7.478 billion in 2015. However, China is still in the middle reaches of the Asia-Pacific region; Japan is dependent on foreign trade due to the long-term impact of the bubble economy, and the domestic value added of its traditional trade exports has declined significantly after 2013, gradually falling from second to fifth. It can be seen that the weighted out degree has played a major role in promoting the decline of Japan’s network status; India is one of the important trading partners of the US ICT industry, and it has also seen rapid growth driven by emerging Asian markets, especially the IT industry. The rapid development of the traditional trade network has accelerated the development of the traditional trade network, and the</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Analysis of the node status of the Asia-Pacific trade network of the ICT industry (top 10)</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  rowspan="2"  >Year</th><th align="center" valign="middle"  colspan="3"  >Traditional trade network (FIN)</th><th align="center" valign="middle"  colspan="3"  >Simple GVC Network (INT)</th><th align="center" valign="middle"  colspan="3"  >Complex GVC network (INTrex)</th></tr></thead><tr><td align="center" valign="middle" >Rank</td><td align="center" valign="middle" >Weighted in-degree</td><td align="center" valign="middle" >Weighted out-degree</td><td align="center" valign="middle" >Rank</td><td align="center" valign="middle" >Weighted in-degree</td><td align="center" valign="middle" >Weighted out-degree</td><td align="center" valign="middle" >Rank</td><td align="center" valign="middle" >Weighted in-degree</td><td align="center" valign="middle" >Weighted out-degree</td></tr><tr><td align="center" valign="middle"  rowspan="10"  >2005</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >USA 44334</td><td align="center" valign="middle" >USA 36950</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >CHN 20334</td><td align="center" valign="middle" >USA 19047</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >CHN 34475</td><td align="center" valign="middle" >JPN 20066</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >CAN 19390</td><td align="center" valign="middle" >JPN 19831</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >USA 16770</td><td align="center" valign="middle" >JPN 13988</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >MYS 11099</td><td align="center" valign="middle" >KOR 16581</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >CHN 17718</td><td align="center" valign="middle" >KOR 15022</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >JPN 7451</td><td align="center" valign="middle" >KOR 11801</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >KOR 9950</td><td align="center" valign="middle" >TWN 15692</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >JPN 11693</td><td align="center" valign="middle" >TWN 12684</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >CAN 7154</td><td align="center" valign="middle" >TWN 10592</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >TWN 8171</td><td align="center" valign="middle" >USA 12755</td></tr><tr><td align="center" valign="middle" >5</td><td align="center" valign="middle" >MEX 6631</td><td align="center" valign="middle" >IND 9425</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >KOR 6486</td><td align="center" valign="middle" >MYS 4716</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >MEX 6616</td><td align="center" valign="middle" >SGP 6844</td></tr><tr><td align="center" valign="middle" >6</td><td align="center" valign="middle" >TWN 5837</td><td align="center" valign="middle" >MYS 7849</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >MEX 3744</td><td align="center" valign="middle" >SGP 4354</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >THA 4035</td><td align="center" valign="middle" >MYS 4630</td></tr><tr><td align="center" valign="middle" >7</td><td align="center" valign="middle" >KOR 4525</td><td align="center" valign="middle" >SGP 6307</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >TWN 3512</td><td align="center" valign="middle" >IND 2971</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >USA 2695</td><td align="center" valign="middle" >THA 2842</td></tr><tr><td align="center" valign="middle" >8</td><td align="center" valign="middle" >AUS 4211</td><td align="center" valign="middle" >CAN 4951</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >AUS 3046</td><td align="center" valign="middle" >THA 2295</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >JPN 2478</td><td align="center" valign="middle" >PHL 1554</td></tr><tr><td align="center" valign="middle" >9</td><td align="center" valign="middle" >MYS 2967</td><td align="center" valign="middle" >THA 3615</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >PHL 2270</td><td align="center" valign="middle" >CAN 2229</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >PHL 1903</td><td align="center" valign="middle" >IDN 1163</td></tr><tr><td align="center" valign="middle" >10</td><td align="center" valign="middle" >THA 2362</td><td align="center" valign="middle" >CHN 2915</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >IND 1910</td><td align="center" valign="middle" >CHN 1384</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >CAN 1504</td><td align="center" valign="middle" >CHN 845</td></tr><tr><td align="center" valign="middle"  rowspan="10"  >2009</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >USA 43100</td><td align="center" valign="middle" >USA 38770</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >CHN 32623</td><td align="center" valign="middle" >USA 17582</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >CHN 37231</td><td align="center" valign="middle" >KOR 17314</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >CHN 30576</td><td align="center" valign="middle" >IND 17242</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >USA 19684</td><td align="center" valign="middle" >KOR 14512</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >KOR 9986</td><td align="center" valign="middle" >JPN 16767</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >CAN 20714</td><td align="center" valign="middle" >KOR 16717</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >JPN 6302</td><td align="center" valign="middle" >JPN 13760</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >MYS 9659</td><td align="center" valign="middle" >TWN 16276</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >JPN 10906</td><td align="center" valign="middle" >JPN 16711</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >CAN 5849</td><td align="center" valign="middle" >TWN 13132</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >MEX 7071</td><td align="center" valign="middle" >USA 11376</td></tr><tr><td align="center" valign="middle" >5</td><td align="center" valign="middle" >MEX 8289</td><td align="center" valign="middle" >TWN 13608</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >KOR 5168</td><td align="center" valign="middle" >IND 7228</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >TWN 6996</td><td align="center" valign="middle" >SGP 7769</td></tr><tr><td align="center" valign="middle" >6</td><td align="center" valign="middle" >AUS 4362</td><td align="center" valign="middle" >MYS 7415</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >AUS 3392</td><td align="center" valign="middle" >SGP 5565</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >THA 3961</td><td align="center" valign="middle" >MYS 5255</td></tr><tr><td align="center" valign="middle" >7</td><td align="center" valign="middle" >TWN 3524</td><td align="center" valign="middle" >SGP 6499</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >MEX 3057</td><td align="center" valign="middle" >MYS 5388</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >USA 2562</td><td align="center" valign="middle" >THA 3337</td></tr><tr><td align="center" valign="middle" >8</td><td align="center" valign="middle" >KOR 3185</td><td align="center" valign="middle" >CAN 5150</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >IND 2520</td><td align="center" valign="middle" >THA 2996</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >PHL 2272</td><td align="center" valign="middle" >PHL 2742</td></tr><tr><td align="center" valign="middle" >9</td><td align="center" valign="middle" >MYS 2462</td><td align="center" valign="middle" >CHN 3981</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >TWN 2498</td><td align="center" valign="middle" >CAN 2786</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >JPN 1697</td><td align="center" valign="middle" >IND 1628</td></tr><tr><td align="center" valign="middle" >10</td><td align="center" valign="middle" >IND 2402</td><td align="center" valign="middle" >THA 3908</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >MYS 2250</td><td align="center" valign="middle" >PHL 2296</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >SGP 1468</td><td align="center" valign="middle" >CHN 1066</td></tr><tr><td align="center" valign="middle"  rowspan="10"  >2015</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >CHN 58716</td><td align="center" valign="middle" >USA 58083</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >CHN 80487</td><td align="center" valign="middle" >KOR 31537</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >CHN 72662</td><td align="center" valign="middle" >KOR 30168</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >USA 47657</td><td align="center" valign="middle" >IND 34743</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >USA 32396</td><td align="center" valign="middle" >TWN 28529</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >KOR 10925</td><td align="center" valign="middle" >TWN 29784</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >CAN 26829</td><td align="center" valign="middle" >KOR 21771</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >JPN 6699</td><td align="center" valign="middle" >USA 24979</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >MYS 7994</td><td align="center" valign="middle" >JPN 15527</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >JPN 16355</td><td align="center" valign="middle" >TWN 20187</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >KOR 6159</td><td align="center" valign="middle" >JPN 16552</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >MEX 6794</td><td align="center" valign="middle" >USA 14421</td></tr><tr><td align="center" valign="middle" >5</td><td align="center" valign="middle" >MEX 10768</td><td align="center" valign="middle" >JPN 14686</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >CAN 5614</td><td align="center" valign="middle" >IND 12791</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >TWN 6996</td><td align="center" valign="middle" >SGP 10355</td></tr><tr><td align="center" valign="middle" >6</td><td align="center" valign="middle" >KOR 5429</td><td align="center" valign="middle" >SGP 9985</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >MYS 3591</td><td align="center" valign="middle" >SGP 9572</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >USA 4365</td><td align="center" valign="middle" >MYS 7134</td></tr><tr><td align="center" valign="middle" >7</td><td align="center" valign="middle" >AUS 4799</td><td align="center" valign="middle" >CHN 7478</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >AUS 3417</td><td align="center" valign="middle" >MYS 8409</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >THA 3899</td><td align="center" valign="middle" >THA 4742</td></tr><tr><td align="center" valign="middle" >8</td><td align="center" valign="middle" >TWN 4032</td><td align="center" valign="middle" >MYS 7380</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >MEX 3368</td><td align="center" valign="middle" >CHN 6209</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >PHL 3210</td><td align="center" valign="middle" >PHL 4669</td></tr><tr><td align="center" valign="middle" >9</td><td align="center" valign="middle" >PHL 3810</td><td align="center" valign="middle" >THA 5667</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >IND 3073</td><td align="center" valign="middle" >THA 5698</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >SGP 2951</td><td align="center" valign="middle" >IND 3265</td></tr><tr><td align="center" valign="middle" >10</td><td align="center" valign="middle" >IND 3740</td><td align="center" valign="middle" >PHL 4597</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >PHL 2174</td><td align="center" valign="middle" >PHL 4813</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >VNM 2946</td><td align="center" valign="middle" >CHN 2640</td></tr></tbody></table></table-wrap><p>domestic value added of traditional trade exports has increased rapidly, that is, it has increased from US $9.425 billion in 2005 to US $34.743 billion in 2015, and the ranking has been increased from fifth to second.</p><p>The weighted in-degree changes in China, India, and Taiwan area, PRC are relatively large. The added value of China’s imports accounted for a relatively high proportion of the total value of imports and exports, indicating that China’s bilateral trade network has grown rapidly, and that the added value of imports from traditional trade networks is an important force that ensures China’s growth as a secondary core in the network. The degree of India’s weighted in-degree has increased, but it is not as good as that of exports. It only increased from US $1.505 billion in 2005 to US $3.74 billion in 2015; Taiwan area, PRC’s weighted in-degree ranking has dropped significantly, and it still forms a pole in the traditional trade network with China and South Korea.</p><p>From the perspective of simple and complex value chain trade networks, from 2005 to 2015, the United States, Japan, South Korea, and Taiwan area, PRC have always occupied the top four positions in the weighted out-degree of the simple and complex value chain trade networks. This shows that these four countries (regions) have always been strong exporters of ICT industry in the Asia-Pacific region, providing a large number of intermediate exports to other countries (regions). In addition, these four countries (regions) have always had a strong competitive relationship. Due to the continuous strengthening of trade links between Taiwan area, PRC, South Korea and Mainland China, after 2009, the weighted out-of-complex value chain and simple value chain trade network began to widen the gap with Japan. Therefore Taiwan area, PRC and South Korea has become China’s two most important trading partners. In the simple trade export degree, Taiwan area, PRC rose from 4th to 2nd, South Korea rose from 3rd to 1st, and China rose to 8th, forming a regional center in the simple value chain trade network. However, Japan’s weighted out-degree ranking dropped from 2nd to 4th, and was surpassed by South Korea and Taiwan area, while the US’s weighted out-degree ranking dropped from 1st to 3rd, indicating the two countries’ status of the simple value chain network has declined, which to a certain extent led to the change of the simple value chain trade network from a unipolar situation in 2005 to a bipolar situation in 2015. In the complex value chain trade network, China’s weighted out-degree ranking has always been around 10th, United States’ network core position is still very strong for its weighted out-degree ranking of the is second only to Japan, South Korea, and Taiwan area, PRC, and is steadily ranked 4th.</p><p>In simple and complex value chain trade networks, the trend of weighted in-degree rankings is quite different from the weighted out-degree rankings. The top three countries (regions) in the weighted in-degree table of simple value chain trade networks are China, the United States, and Japan. The top three countries (regions) in the weighted in-degree of complex value chain trade networks are China, South Korea and Malaysia. China has always been the largest importer of ICT industry simple value chain trade in the Asia-Pacific region, because a large amount of processing trade has promoted China to become the largest regional center. The United States and South Korea have maintained their simple and complex top three positions respectively. Therefore, China and the United States have formed a bipolar situation of simple value chain trade networks. In the simple value chain trade network weighted in-degree, South Korea’s weighted in-degree has gradually surpassed that of Japan in the past 11 years, which can explain the changes in the status of the two countries in the simple value chain network to a certain extent. In addition, Malaysia’s weighted in-degree ranking has risen to sixth, making it a more important country in the sub-peripheral region; Malaysia has become a more important country in the core region in the weighted in-degree of complex value chain trade networks. This status of Malaysia is quite different from that in the traditional trade network and simple value chain trade network.</p></sec><sec id="s4_3"><title>4.3. Analysis on the Evolution Trend of the Asia-Pacific Trade Network of the ICT Industry</title><p>1) Traditional trade network</p><p>As shown in <xref ref-type="fig" rid="fig4">Figure 4</xref>, the ICT industry’s Asia-Pacific traditional trade network structure center is constantly changing, and the regional center is changing from unipolar to multipolar. Before 2009, the United States was the regional center of the traditional trade network structure. Trade in the region basically revolved around the United States while the degree of trade linkages varies. Canada and India trade the most closely with the United States, followed by China, Japan, South Korea, and Taiwan area, PRC, while the trade links with Singapore, Mexico, Malaysia and the core regional economies are relatively weak, and seven countries and regions including Russia are in a marginal position. The occurrence of the subprime mortgage crisis in 2008 has changed the regional structure, for China’s positive incentive policies has enhanced its ICT industry importance in the network. In 2009, the total import and export volume of China’s traditional trade network surpassed Japan for the first time.</p><p>In 2015, the structure of the traditional trade network of the ICT industry in the Asia-Pacific region has undergone fundamental changes: the traditional trade of some countries in the region has shifted; the degree of interdependence of the trade network has been scattered; and the trade network has developed from one center to multiple core regions. The first is the core area of the trade network centered on the United States, including Canada, India, Mexico and other countries. China’s economy continues to improve with the ICT industry further opened, and the import and export trade continues to increase, attracting countries and regions in the region. Therefore, the focus of trade has gradually shifted to China, forming the second core area of trade network centered on China, including South Korea, Japan, Taiwan area, PRC and other countries and regions.</p><p>2) Value chain trade network</p><p>As shown in <xref ref-type="fig" rid="fig5">Figure 5</xref>, in the complex value chain trade network, China, as the center of the trade network, has the closest ties with Japan, South Korea, Taiwan area, PRC and the United States, forming the core area of the complex value chain trade network, while Mexico, the Philippines, Singapore and Thailand</p><p>have slightly weaker trade intensity with China and are in the sub-peripheral area. The other seven countries (regions) are at the edge of the network.</p><p>After 2009, the structure of the complex value chain trade network has undergone certain changes. First of all, the trade intensity between South Korea, Taiwan area, PRC, and China is gradually widening the gap with Japan. These two economies have become China’s most important trading partners; although the United States and Malaysia still form the core area of the network around China, the volume of trade in Malaysia surpassed the United States for the first time, and its status rose in the Asia-Pacific region; the sub-peripheral countries, dominated by Mexico, Thailand and Singapore, also have a tendency to move closer to the core region. In 2015, most countries (regions) in the Asia-Pacific complex value chain trade value chain network structure of the ICT industry stabilized, and their statuses have not changed significantly. In the complex value chain trade network, only Japan further declined in 2013, from China’s most important trading partner in 2005 to a position close to that of the United States and Malaysia. The trade ties between mainland China, South Korea and Taiwan</p><p>area, PRC, have been strengthened day by day, and these three economies have gradually formed secondary core areas of complex value chain trade networks outside the United States and Japan.</p></sec></sec><sec id="s5"><title>5. Conclusions and Recommendations</title><p>This article uses social network analysis methods, based on the added value data of the World Input-Output Tablefrom 2005 to 2015, to portray the Asia-Pacific trade network of the ICT industry. It also analyzes the variation trend of traditional trade, simple and complex value chain trade, the evolution of trade network structure, the weighted out-degree and the weighted in-degree of trade network and the following conclusions are drawn.</p><p>First, the overall structure of the ICT industry trade network in the Asia-Pacific region is stable. During the evolution of traditional trade networks and value chain trade networks, the development of traditional trade networks and value chain trade networks are generally stable, and regional trade links are gradually becoming closer; both traditional trade networks and value chain trade networks reflect regional characteristics, which is consistent with the research conclusions of the core—sub-periphery—peripheral trade network characteristics reflected in the previous literature; traditional trade networks and value chain trade networks will gradually recover when they are subjected to external shocks, and the impact of the shocks is basically regional, temporary and phased, but the traditional trade network and the value chain trade network reflect slightly different recovery status.</p><p>Second, the importance of ICT industry trade network nodes in the Asia-Pacific region has changed. Traditional trade networks and value chain trade networks are evolving, and their structures are constantly changing, showing a situation of ebb and flow, with regional centers changing from unipolar to multipolar. The center of the traditional trade network is gradually being weakened or replaced, and the degree of dependence on the trade network is scattered; the position of the trade network center of the value chain is also changing. The ICT industry in the Asia-Pacific region has formed the core area of the trade network centered on the United States and China in the traditional trade network; in the process of changes in the simple and complex value chain trade network structure, China has responded to crises by stimulating the economy, and increasing trade in intermediate goods, which enabling China to surpass other countries (regions) in the Asia-Pacific region in value chain trade and become the center of the value chain trade network.</p><p>Third, the trade network of the ICT industry in the Asia-Pacific region has strengthened. In the evolution of traditional trade networks and value chain trade networks, trade networks are interdependent and closely connected around the core of the region. The closeness and strength of the connections mainly depend on the regional position of the trade network and the economic policies of the core countries and strong development momentum. China has taken active measures in response to external shocks and strengthened cooperation, increased currency injection to stimulate the economy and lead the world economy out of difficulties, thus countries have maintained close trade ties with China in order to get rid of these difficulties. Therefore, the value-added trade network of the ICT industry value chain in the Asia-Pacific region has shown rapid growth, and it maintains the strongest trade links and high trade intensity in the network with other countries, and has a relatively central position in the value chain trade network.</p><p>Based on the analysis and research conclusions of this article and in order to promote the development of value-added trade in China’s ICT industry, this article puts forward the following suggestions: first, China should base on the domestic trade network, to advance the domestic economy, industrial chain, and technological innovation, in order to form its own central network nodes, get rid of excessive dependence on a single international trade network. Also China needs to seek diversified international cooperation and multi-regional cooperation so as to reduce the impact of external shocks. Second, promote the international regional cycle, prioritize the development of trade network cooperation with neighboring regions with strong interdependence and strong trade complementarity. Additionally, China needs to shorten supply chains, extend value chains, ensure a virtuous circle of trade, and improve trade network connections. Third, ensure the continuous opening of the ICT industry, connect with high-level free trade rules, enhance the core competitiveness of the domestic ICT industry, increase cooperation between enterprises, extend the industrial chain, and form closer complementary relationships.</p></sec><sec id="s6"><title>Funding</title><p>The research was supported by the financial support from the Chinese National Research of Social Sciences Youth funded projects (No. 18CGJ005).</p></sec><sec id="s7"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s8"><title>Cite this paper</title><p>Huang, Y. X., &amp; Tang, Q. M. (2021). Research on the Structural Characteristics and Evolution of the Asia-Pacific Trade Network of the ICT Industry. American Journal of Industrial and Business Management, 11, 1071-1088. https://doi.org/10.4236/ajibm.2021.1111065</p></sec><sec id="s9"><title>NOTES</title></sec></body><back><ref-list><title>References</title><ref id="scirp.112969-ref1"><label>1</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Chen</surname><given-names> Y. F. </given-names></name>,<etal>et al</etal>. (<year>2011</year>)<article-title>. Social Network Analysis of the World Trade Pattern from 2000 to 2009</article-title><source> Journal of International Trade</source><volume> 11</volume>,<fpage> 31</fpage>-<lpage>42</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.112969-ref2"><label>2</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Cheng</surname><given-names> S. J.</given-names></name>,<name name-style="western"><surname> &amp; Wang</surname><given-names> Z. J. </given-names></name>,<etal>et al</etal>. (<year>2011</year>)<article-title>. Research on the Evolution of World Crude Oil Trade Spatial Pattern under Complex Network Theory</article-title><source> Scientia Geographica Sinica</source><volume> 31</volume>,<fpage> 1342</fpage>-<lpage>1348</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.112969-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">He, Z., Yang, Y., Liu, Y. et al. (2019). The Evolutionary Characteristics of the World Energy Trade Network and the Relationship between Energy Competition and Cooperation. Progress in Geography, 38, 177-188. https://doi.org/10.18306/dlkxjz.2019.10.016</mixed-citation></ref><ref id="scirp.112969-ref4"><label>4</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Jiang</surname><given-names> X. R.</given-names></name>,<name name-style="western"><surname> Yang</surname><given-names> Y. C.</given-names></name>,<name name-style="western"><surname> &amp; Wang</surname><given-names> S. L. </given-names></name>,<etal>et al</etal>. (<year>2018</year>)<article-title>. The Temporal and Spatial Evolution of the Global Trade Network Pattern from 1985 to 2015 and Its Enlightenment to China’s Geostrategy</article-title><source> Geographical Research</source><volume> 37</volume>,<fpage> 495</fpage>-<lpage>511</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.112969-ref5"><label>5</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Liu</surname><given-names> J. </given-names></name>,<etal>et al</etal>. (<year>2013</year>)<article-title>. Research on the Evolution of International Crude Oil Trade Pattern Based on Social Networks</article-title><source> Journal of International Trade</source><volume> 12</volume>,<fpage> 48</fpage>-<lpage>57</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.112969-ref6"><label>6</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Liu</surname><given-names> J. S. </given-names></name>,<etal>et al</etal>. (<year>2016</year>)<article-title>. The Evolution of World Natural Gas Trade Pattern Based on Social Network Analysis</article-title><source> Economic Geography</source><volume> 36</volume>,<fpage> 89</fpage>-<lpage>95</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.112969-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">Shen, H. R. (2019). Research on ICT Industry Global Value Chain Position Measurement and Climbing Mechanism. Dongbei University of Finance and Economics.</mixed-citation></ref><ref id="scirp.112969-ref8"><label>8</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Song</surname><given-names> Z. Y.</given-names></name>,<name name-style="western"><surname> Che</surname><given-names> S. Y.</given-names></name>,<name name-style="western"><surname> &amp; Yang</surname><given-names> Y. </given-names></name>,<etal>et al</etal>. (<year>2017</year>)<article-title>. The Topological Relationship between the “Belt and Road” Trade Network and the Global Trade Network</article-title><source> Progress in Geography</source><volume> 11</volume>,<fpage> 22</fpage>-<lpage>30</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.112969-ref9"><label>9</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Sun</surname><given-names> X. L.</given-names></name>,<name name-style="western"><surname> Yang</surname><given-names> Y. Y.</given-names></name>,<name name-style="western"><surname> &amp; Wu</surname><given-names> D. S. </given-names></name>,<etal>et al</etal>. (<year>2012</year>)<article-title>. Global Crude Oil Trade Network Topology and Evolution Characteristics Identification</article-title><source> World Economy Studies</source><volume> 9</volume>,<fpage> 13</fpage>-<lpage>19+89</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.112969-ref10"><label>10</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Wang</surname><given-names> X.</given-names></name>,<name name-style="western"><surname> Qiang</surname><given-names> W. L.</given-names></name>,<name name-style="western"><surname> Niu</surname><given-names> S. W. et al. </given-names></name>,<etal>et al</etal>. (<year>2018</year>)<article-title>. Global Agricultural Product Trade Network and Its Evolution Analysis</article-title><source> Journal of Natural Resources</source><volume> 33</volume>,<fpage> 940</fpage>-<lpage>953</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.112969-ref11"><label>11</label><mixed-citation publication-type="other" xlink:type="simple">Wang, Z., Wei, S. J., &amp; Zhu, K. (2013). Quantifying International Production Sharing at the Bilateral and Sector Levels. NBER Working Papers. https://doi.org/10.3386/w19677</mixed-citation></ref><ref id="scirp.112969-ref12"><label>12</label><mixed-citation publication-type="other" xlink:type="simple">Wang, Z., Wei, S. J., &amp; Zhu, K. F. (2015). Total Trade Calculation: Official Trade Statistics and Measurement of Global Value Chains. Chinese Social Sciences, No. 9, 108-127.</mixed-citation></ref><ref id="scirp.112969-ref13"><label>13</label><mixed-citation publication-type="other" xlink:type="simple">Wang, Z., Wei, S. J., Yu, X. et al. (2017). Measures of Participation in Global Value Chains and Global Business Cycles. Social Science Electronic Publishing. https://doi.org/10.3386/w23222</mixed-citation></ref><ref id="scirp.112969-ref14"><label>14</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Xu</surname><given-names> H. L.</given-names></name>,<name name-style="western"><surname> Sun</surname><given-names> T. Y.</given-names></name>,<name name-style="western"><surname> &amp; Cheng</surname><given-names> L. H. </given-names></name>,<etal>et al</etal>. (<year>2015</year>)<article-title>. “One Belt One Road” High-End Manufacturing Trade Pattern and Influencing Factors Research-Based on Complex Network Index Random Graph Analysis</article-title><source> Finance &amp; Trade Economics</source><volume> 12</volume>,<fpage> 74</fpage>-<lpage>88</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.112969-ref15"><label>15</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Yang</surname><given-names> W. L.</given-names></name>,<name name-style="western"><surname> Du</surname><given-names> D. B.</given-names></name>,<name name-style="western"><surname> Ma</surname><given-names> Y. H.</given-names></name>,<name name-style="western"><surname> &amp; Jiao</surname><given-names> M. Q. </given-names></name>,<etal>et al</etal>. (<year>2018</year>)<article-title>. The Spatial Structure and Proximity of the Trade Network of Countries along the “Belt and Road”</article-title><source> Geographical Research</source><volume> 37</volume>,<fpage> 2218</fpage>-<lpage>2235</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.112969-ref16"><label>16</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Zhang</surname><given-names> Q.</given-names></name>,<name name-style="western"><surname> &amp; Li</surname><given-names> H. Y. </given-names></name>,<etal>et al</etal>. (<year>2012</year>)<article-title>. An Empirical Study on the Change of China’s Role in International Trade since My Country’s Entry into WTO—Based on the Method of Social Network Analysis</article-title><source> Journal of Finance and Economics</source><volume> 10</volume>,<fpage> 79</fpage>-<lpage>89</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref></ref-list></back></article>