Research on the Structural Characteristics and Evolution of the Asia-Pacific Trade Network of the ICT Industry —From the Perspective of Global Value Chain

The ICT industry has gradually become an important industry in the regional economy. The global traditional, simple and complex value chain trade network has undergone fundamental changes during the evolution process, which has changed the overall pattern of the global value chain trade network. This article 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 visualiza-tion software Gephi to analyze the evolution characteristics of the 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 helped 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.


Introduction
The ICT industry is a new technology field formed by the integration of the in-

Literature Review
The social network analysis method has been widely used in the field of interna-  . 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 & 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;Song et al., 2017;Jiang et al., 2018;He et al., 2019). However, the statistical methods based on total value trade have serious shortcomings and cannot reflect the true situation of trade gains (Wang et al., 2015), especially in industries with high value-added differences in various links such as ICT. It is necessary to portray the regional trade network from the perspective of global value chain.
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.

Network Construction Method
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

Data Sources
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 de- which is processed based on the public released OECD-ICIO2018 tables, and the WWZ algorithm proposed by Wang et al. (2013) andWang Zhi et al. (2015).
Based on the input-output perspective, further decomposition of total trade ex- ing 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.
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).
According to the meaning of the above DVA sub-items, it can be found that

1) Construction of nodes
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: 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: In this formula, out i W represents the weighted outdegree, and in i W represents the weighted indegree.

Characteristics and Evolution Trends of the Asia-Pacific
Trade Network of the ICT Industry 2) Characteristics of total import and export volume of simple and complex value chain trade

Characteristics of the Total Import and Export Volume of the Asia-Pacific Trade Network of the ICT Industry
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 (

Analysis of the Characteristics of the Asia-Pacific Trade Network of the ICT Industry
In the Asia-Pacific trade network of the ICT industry, the status and importance    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.

1) Traditional trade network
As shown in Figure 4, 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

Conclusions and Recommendations
This article uses social network analysis methods, based on the added value data of the World Input-Output Table from 2005  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 Y. X. Huang, Q. M. Tang