International Competitiveness of China’s Manufacturing Sectors:Estimation Based on Trade in Value-added

Based on trade in value-added, this paper has estimated the revealed comparative advantage （RCA） of China＇s various manufacturing sectors between 1995 and 2011 and compared with the RCA indexes measured using conventional aggregate accounting approach. Results indicate that： （1） the RCA index measured using conventional aggregate accounting approach has underestimated China＇s comparative advantage of labor-intensive sectors but overestimated China＇s comparative advantage in capital, knowledge and technology-intensive manufacturing sectors, giving rise to a serious misjudgment. （2） The RCA measured using value-added approach shows that in the industry chain layout of global manufacturing sectors, China＇s comparative advantage is still concentrated in labor-intensive manufacturing sectors but has signs of weakening; in capital, knowledge and technology-intensive sectors, China is yet to develop any significant comparative advantage; there are signs that China is developing comparative advantage in capital-intensive sectors yet China＇s comparative disadvantage in knowledge and technology-intensive sectors has no significant tendency to improve. This result not only helps correct the misjudgment of China＇s competitiveness in manufacturing sectors based on conventional aggregate accounting approach but offers important policy implications for setting strategic directions and policies for China＇s manufacturing transition and upgrade.

Local Trade Networks among Farmers and Traders

Both farmers and traders benefit from trade networking, which is crucial for the local economy. Therefore, it is crucial to understand how these networks operate, and how they can be managed more effectively. Throughout this study, we examine the economic networks formed between farmers and traders through the trade of food products. These networks are analyzed from the perspective of their structure and the factors that influence their development. Using data from 18 farmers and 15 traders, we applied exponential random graph models. The results of our study showed that connectivity, Popularity Spread, activity spread, good transportation systems, and high yields all affected the development of networks. Therefore, farmers’ productivity and high market demand can contribute to local food-crop trade. The network was not affected by reciprocity, open markets, proximity to locations, or trade experience of actors. Policy makers should consider these five factors when formulating policies for local food-crop trade. Additionally, local actors should be encouraged to use these factors to improve their network development. However, it is important to note that these factors alone cannot guarantee success. Policy makers and actors must also consider other factors such as legal frameworks, economic policies, and resource availability. Our approach can be used in future research to determine how traders and farmers can enhance productivity and profit in West Africa. This study addresses a research gap by examining factors influencing local food trade in a developing country.

Prosecution records reveal pangolin trading networks in China, 2014–2019

In a precautionary response to the current coronavirus(COVID-19)pandemic,China’s Ministries permanently banned eating and trading in terrestrial wild(non-livestock)animals on 24 February 2020,and extensively updated the list of Fauna under Special State Protection(LFSSP)in 2020 and 2021,in which pangolins(Manidae spp.)were upgraded to the highest protection level.Examining 509 pangolin prosecution records from China Judgements online prior to these changes(01/01/14–31/12/19),we identified that Guangdong,Guangxi and Yunnan Provinces were hotspots for trade in whole pangolins and their scales.

Exploring the complex structural evolution of global primary product trade network

The production and trade of primary products had a growing impact on the economic security of all countries and regions,and the strategic position of these products in the global trade network was becoming increasingly prominent.Based on complex network theory,this paper explored the spatial pattern and complex structural evolution of the global primary product trade network(GPPTN)during 1985-2015 by using index methods,such as centrality,Sankey diagram,and structure entropy,focusing on the diversified spatial structure of China’s import and export markets for primary products(with exceptions of Taiwan of China,Hong Kong of China,and Macao of China due to a lack of data)and their geographical implications for China’s energy security.The research offered the following key findings.The GPPTN showed an obvious spatial heterogeneity pattern,and the area of import consumption was more concentrated;however,the overall trend was decentralized.The trade center of gravity shifted eastwards and reflected the rise of emerging markets.The overall flow of the GPPTN was from west to east and from south to north.In terms of the community detection of the GPPTN,North America,Europe,and Asia increasingly presented an unbalanced“tripartite confrontation”.China’s exports of primary products were mainly concentrated in the Association of Southeast Asian Nations(ASEAN)and other peripheral regions of Asia,and its imports undergone a major transformation,gradually expanding from the peripheral regions of Asia to Africa,the Middle East,Latin America,and other parts of the world.Energy fuels also became the largest imported primary products.Based on the changing trend of structural entropy and main market share,the analysis showed that the stable supply of China’s energy diversification was gradually realized.In particular,the cooperation dividend proposed by the Belt and Road initiative became an important turning point and a strong support for the expansion of China’s energy market diversification pattern and guarantee of energy security.

Spatial Interaction Network Analysis of Crude Oil Trade Relations between Countries along the Belt and Road

Based on the theories and methods of complex network,crude oil trade flows between countries along the Belt and Road(B&R,hereafter)are inserted into the Geo-space of B&R and form a spatial interaction network which takes the countries as nodes and takes the trade relations as edges.The networked mining and evolution analysis can provide important references for the research on trade relations among the B&R countries and the formulation of trade policy.This paper researches and discusses the construction,statistical analysis,top networks and stability of the crude oil trade network between the B&R countries from 2001 to 2020 from the perspectives of Geo-Computation for Social Sciences(GCSS)and spatial interaction.Firstly,evolutions of out-degree,in-degree,out-strength and in-strength of the top 10 countries in the crude oil trade network are computed and analyzed.Secondly,the top network method is used to explore the evolution characteristics of hierarchical structures.And finally,the sequential evolution characteristics of the crude oil trade network stability are analyzed utilizing the network stability measure method based on the trade relationship autocorrelation function.The analysis results show that Russia has the largest out-degree and out-strength,and China has the largest in-degree and in-strength.The crude oil trade volume of the top 10 import and export networks between 2001—2020 accounts for over 90%of the total trade volume of the crude oil trade network,and the proportion remains relatively stable.However,the stability of the network showed strong fluctuations in 2009,2012 and 2014,which may be closely related to major international events in these years,which could furtherly be used to build a correlation model between network volatility and major events.This paper explores how to construct and analyze the spatial interaction network of crude oil trade and can provide references for trade relations research and trade policy formulation of B&R countries.

Identification of the Credit Guarantee Network of Steel Trade Enterprises in China

The risk points in the credit guarantee network of steel trade enterprises were identified by using the network analysis method in this paper. Firstly, the formation and operation mechanism of steel trade credit guarantee network was analyzed.Secondly,a guarantee network was established to analyze the related network structure indexes based on the mutual guarantee data of 83 enterprises in a steel trade market. These indexes included centrality,honest broker,and structural hole. The results suggest that network analysis method can be used to find out the risk points of the guarantee network. Additionally,some recommendations are brought forth to reduce or prevent future crises.

Export Value-Added of China’s Manufacturing Sector:Estimation and Mechanism Analysis

Estimation of domestic and overseas value-added of manufacturing sector is an important and difficult subject for the science-based evaluation of a country＇s trade interests under global value chain. Traditional HIY approach overestimates the domestic value- added of export. Although Koopman＇s method made certain improvements, it cannot utilize traditional I/O matrix and direct input coefficient matrix under the condition of incomplete information. By creating GAMS model, this paper addresses the above-mentioned problems and employs an improved model for the estimation of variations in domestic and overseas value-added of Chinese exports between 2002 and 2012. Our results indicate that by neglecting the export of processing trade, HIY approach overestimates the domestic value- added ratio of Chinese exports. As more imported intermediate inputs have been used in the export of processing trade, the estimation result of this paper have corrected deviations in the forecast of overseas value-added ratio and its tendencies based on HIY method Further analysis of specific factors of domestic value-added of export led to the discovery that the domestic value-added of export of processing trade and mixed trade is highly vulnerable to the impact of international capital inflow. It can be seen that the improved method for the estimation of value-added has indeed corrected the deviations in the estimation of China＇s value-added. In conclusion, China should accelerate the development of export of non- processing trade and trade in high-end services, and balance the relationship of export between local firms and foreign-funded firms, with a view to improving trade dependence and increasing the trade status of Chinese manufaeturing firms in global value chain.

Measuring Global Supply Chain Vulnerabilities Using Trade Network Analysis Method

With the trade network analysis method and bilateral country-product level trade data of 2017-2020,this paper reveals the overall characteristics and intrinsic vulnerabilities of China’s global supply chains.Our research finds that first,most global supply-chain-vulnerable products are from technology-intensive sectors.For advanced economies,their supply chain vulnerabilities are primarily exposed to political and economic alliances.In comparison,developing economies are more dependent on regional communities.Second,China has a significant export advantage with over 80%of highly vulnerable intermediate inputs relying on imports of high-end electrical,mechanical and chemical products from advanced economies or their multinational companies.China also relies on developing economies for the import of some resource products.Third,during the trade frictions from 2018 to 2019 and the subsequent COVID-19 pandemic,there was a significant reduction in the supply chain vulnerabilities of China and the US for critical products compared with other products,which reflects a shift in the layout of critical product supply chains to ensure not just efficiency but security.China should address supply chain vulnerabilities by bolstering supply-side weaknesses,diversifying import sources,and promoting international coordination and cooperation.

Research on Weighted Directed Dynamic Multiplexing Network of World Grain Trade Based on Improved MLP Framework

As the main food source for humans, the global movement of the three major grains significantly impacts human survival and development. To investigate the evolution of the world cereal trade network and its development trend, a weighted directed dynamic multiplexed network was established using historical data on cereal trade, cereal import dependency ratio, and arable land per capita. Inspired by the MLP framework, we redefined the weight determination method for computing layer weights and edge weights of the target layer, modified the CN, RA, AA, and PA indicators, and proposed the node similarity indicator for weighted directed networks. The AUC metric, which measures the accuracy of the algorithm, has also been improved in order to finally obtain the link prediction results for the grain trading network. The prediction results were processed, such as web-based presentation and community partition. It was found that the number of generalized trade agreements does not have a decisive impact on inter-country cereal trade. The former large grain exporters continue to play an important role in this trade network. In the future, the world trade in cereals will develop in the direction of more frequent intercontinental trade and gradually weaken the intracontinental cereal trade.

Changes of China's Position in the World Food Trade Network

"Ensuring stability in foreign trade"and"ensuring food security"are essential parts of China's"six priorities"and"stability in six areas".Based on the data of bilateral food trade between countries during 1996-2018,using descriptive statistical analysis and social network analysis methods,this paper analyzed the changes of China's trade position in the world food trade network.It reached the following results.(i)China's position in the trade network has undergone a phased process of"remarkable improvement-continuous fluctuation-significant decline-steady growth".(ii)Export participation is better than import participation,the gap between trade export strength and import strength is widening,and the effective scale and constraint index gradually improve.(iii)The change of China's position in the food trade network is affected by geographical,economic,institutional and cultural factors.In view of these findings,it is recommended to improve node centrality,enhance network participation,improve network interconnection,and prevent international market risks,so as to better deal with the complex international environment.

Territory-based and Ownershipbased Gains from Trade under the Global Production Network——An Empirical Study Based on China

Under global production network,export cannot represent a country's gains from trade,and territory-based gains from trade refer to the remainder of export after deducting the input of intermediate goods and re-export after value-added return.Ownership-based gains from trade refer to the remainder of territory-based gains from trade after further deducting the trade in value added(TVA) realized through the inflow of foreign factors.By creating a multicountry input and output model,this paper calculates the territory-based gains from trade,ownership-based gains from trade,and territory-based gains from trade for foreign countries realized through China's export,as well as valueadded return and territory-based gains from trade for foreign countries realized through China's import.This paper has arrived at the following conclusions:behind China's status as the largest goods exporting country in the world,most of Chinese exports contribute to the gains of foreign countries;value addition for foreign countries realized through China's export and value-added return realized through China's import mostly come from Taiwan region,Japan and South Korea in East Asia;a considerable part of gains from trade for the United States realized through China-US trade is achieved through indirect trade.

Study on the Influence of Network Economy on International Economy and Trade

Research and development and popularization of the internet and other information technologies have accelerated the development rate of Chinese e-commerce industry while at the same time, bringing forward the arrival of the network economy era. Therefore, a study on the economy and trade model under the network economy era shall be conducted for a higher level of Chinese international economy and trade. In view of this, this paper mainly provides a brief overview of the network economy, and deeply analyzes both the positive and negative impacts of the network economy on the international economy and trade. Thus, on this basis, a deep study on specific ways of optimizing the international economy and trade under the background of the network economy has been carried out to further raise the development level of Chinese international economy and trade with the development guarantee for Chinese national economy.

Temporal and spatial evolution of global major grain trade patterns

The complex and volatile international landscape has significantly impacted global grain supply security. This study uses a complex network analysis model to examine the evolution and trends of the global major grain trade from 1990 to 2020, focusing on network topology, centrality ranking, and community structure. There are three major findings. First, the global major grain trade network has expanded in scale, with a growing emphasis on diversification and balance. During the study period, the United States, Canada, China, and Brazil were the core nodes of the network. Grain-exporting countries were mainly situated in Asia, the Americas, and Europe, and importing countries in Asia, Africa, and Europe. Second, a significant increase in the number of high centrality countries with high export capacity occurred, benefiting from natural advantages such as fertile land and favorable climates. Third, the main global grain trade network is divided into four communities, with the Americas-Europe community being the largest and most widespread. The formation of the community pattern was influenced by geographic proximity, driven by the core exporting countries. Therefore, the world needs to enhance the existing trade model, promote the multi-polarization of the grain trade network, and establish a global vision for the future community. Countries and regions should participate actively in global grain trade security governance and institutional reform, expand trade links with other countries, and optimize import and export policies to reduce trade risks.

The Impact of the Network Trade Era on the Chinese(Asian)Economy

With the rapid development of the Internet and information technology,network trade has emerged and broken through the traditional trade boundaries in the rapidly developing information technology.Therefore,with the advent of the information age,network trade has had a series of impacts on China’s economy,which has given wings to the take-off of China’s economy,but also made the development of China’s economy face a new environment and new challenges.Based on this,this paper first analyzes the connotation of network trade,and analyzes the impact of the network trade era on China’s economy.Through such a study,it aims to make China better seize the opportunities of the times and meet the challenges of the times in the process of promoting social and economic development,so as to achieve a good and rapid development of the national economy.

Re-Evaluation of China＇s Service Trade Competitiveness： A Global Value Chain Perspective

Based on the Worm Input-Output Database （WIOD）, this paper conducts a forward-linkage decomposition of value-added in trade to estimate China＇s service value-added exports and its service sector＇s international competitiveness during 2000- 2014. Result indicates that during the sample period, China＇s service exports measured by forward-linkage decomposition method accounted for around 35% in its total export. While the value of services exported directly through the service sector accounted for a falling share, the value of services exported through other sectors represented an increasing share. China ranks second in the world in terms of market share of service exports. However, the revealed comparative advantage （RCA） of China＇s service exports and export sophistication remains limited.

Evolutionary characteristics of export trade network in the Arctic region

The economic potential induced by environmental changes in the Arctic region garnered substantial interest,which positions Arctic trade as a crucial indicator in forecasting the impacts of climate change on the global economy.Nevertheless,attention devoted to the evolving dynamics of trade in the Arctic region remains scarce.In this study,we constructed export trade network in the Arctic region(including Denmark,Finland,Sweden,Norway,Iceland,the Canadian Arctic,the Russian Arctic,Alaska State of the USA,and Greenland)from 1990 to 2019 and analyzed its topology and evolutionary characteristics through complex network theory.We used a structural entropy index based on the distribution of the number of trading partners and the degree of trade concentration to assess export diversity,while we also utilized a revealed comparative advantage index to evaluate product export competitiveness using the share of trade volume of each type of product.The results indicate that the total export trade in the Arctic region increased by 53.4%during 1990-2019,with the most significant growth observed in the exports of chemical products and mineral fuels.The increasing complexity of trade network in the Arctic region resulted in the region’s export destinations no longer being concentrated on a few major countries and regions.The proportion of exports from the Arctic region to Europe decreased by 13.5%,while the proportion of exports from the Arctic region to Asia and North America increased by 6.8%and 3.1%,respectively.The Arctic region exhibited clear distinctions in the range of flows of different products,and its export trade was becoming increasingly diversified.Although differences in comparative advantages between products within individual countries or regions have narrowed,substantial gaps persist.The findings of this study can enhance the comprehensive understanding of the significance and function of Arctic trade activities within the global economy,providing a scientific basis for addressing the associated challenges and opportunities in the context of climate change.

Cost-Minimized Virtual Elastic Optical Network Provisioning with Guaranteed QoS

Network virtualization is important for elastic optical networks(EONs)because of more flexible service provisioning.To ensure guaranteed quality of service(QoS)for each virtual elastic optical network(VEON),clients usually request network resources from a network operator based on their bandwidth requirements predicted from historical traffic demands.However,this may not be efficient as the actual traffic demands of users always fluctuate.To tackle this,we propose a new VEON service provisioning scheme,called SATP,which consists of three stages,i.e.,spectrum assignment(SA),spectrum trading(ST),and spectrum purchasing(SP).Unlike conventional once-for-all VEON service provisioning approaches,the SATP scheme first allocates spectrum resources to VEONs according to their predicted bandwidth requirements with a satisfaction ratio α(0<α≤1).Then,to minimize service degradation on VEONs which are short of assigned spectra for their peak traffic periods,the scheme allows VEONs to trade spectra with each other according to their actual bandwidth requirements.Finally,it allows VEON clients to purchase extra spectrum resources from a network operator if the spectrum resources are still insufficient.To optimize this entire process,we formulate the problem as a mixed integer linear programming(MILP)model and also develop efficient heuristic algorithms for each stage to handle large test scenarios.Simulations are conducted under different test conditions for both static and dynamic traffic demand scenarios.Results show that the proposed SATP scheme is efficient and can achieve significant performance improvement under both static and dynamic scenarios.

Hot Events Detection of Stock Market Based on Time Series Data of Stock and Text Data of Network Public Opinion

With the highly integration of the Internet world and the real world, Internet information not only provides real-time and effective data for financial investors, but also helps them understand market dynamics, and enables investors to quickly identify relevant financial events that may lead to stock market volatility. However, in the research of event detection in the financial field, many studies are focused on micro-blog, news and other network text information. Few scholars have studied the characteristics of financial time series data. Considering that in the financial field, the occurrence of an event often affects both the online public opinion space and the real transaction space, so this paper proposes a multi-source heterogeneous information detection method based on stock transaction time series data and online public opinion text data to detect hot events in the stock market. This method uses outlier detection algorithm to extract the time of hot events in stock market based on multi-member fusion. And according to the weight calculation formula of the feature item proposed in this paper, this method calculates the keyword weight of network public opinion information to obtain the core content of hot events in the stock market. Finally, accurate detection of stock market hot events is achieved.

The Effect of Price Discount on Time-Cost Trade-off Problem Using Genetic Algorithm

Time-cost trade off problem (TCTP), known in the literature as project crashing problem (PCP) and project speeding up problem (PSP) is a part of project management in planning phase. In this problem, determining the optimal levels of activity durations and activity costs which satisfy the project goal(s), leads to a balance between the project completion time and the project total cost. A large amount of literature has studied this problem under various behavior of cost function. But, in all of them, influence of discount has not been in-vestigated. Hence, in this paper, TCTP would be studied considering the influence of discount on the re-source price, using genetic algorithm (GA). The performance of proposed idea has been tested on a medium scale test problem and several computational experiments have been conducted to investigate the appropriate levels of proposed GA considering accuracy and computational time.