The evolution of global soybean trade network pattern based on complex network

China experiences a serious shortage of soybean supplies and relies heavily on international trade with high vulnerability and large uncertainty, which maybe sows food security risks. It is of great significance to analyze the structural evolution of the global soybean trade network and its implications to China for ensuring food security. This paper constructed a global soybean trade network (GSTN) and analyzed the structural evolutionary characteristics of GSTN from 2000 to 2020 using the complex network analysis method and simulated the impact of targeted destruction on China through scenario analysis. The results showed that GSTN was gradually complex exhibiting a small word and a scale-free network property. The global soybean exporter was dominated by some major soybean-producing countries in America. The US played an important role in maintaining GSTN’s robustness. China was the world’s largest soybean importer; unfortunately, its soybean imports relied heavily on a few countries, and the anti-interference ability of China’s soybean trade tended to decline. Therefore, China’s soybean trade was increasingly vulnerable to being tightly controlled by other countries when some uncertain factors occurred, such as trade frictions and changes in policy decisions from importing and exporting countries. The US and Brazil were key countries with significant soybean trade ties to China. To assess the impact of the two countries on China’s soybean trade, targeted destruction method was used through destroying them in the network. Targeted destruction scenario analysis indicated the two countries played important roles in the anti-interference ability of China’s soybean trade. Brazil played a positive role in China’s control of soybean trade flows, while the US did not. Some policies for China’s soybean production and international trade were proposed. A balance between the domestic production and import of soybean is needed. Optimizing the soybean trade import system and seeking more trade partners is crucial. Improving soybean self-sufficiency is the fundamental way to reduce the high-import dependence. The study provided some insights for coping with international market fluctuations and improving the sustainability of China’s soybean trade.

IntroductionThe global beef trade, as a critical component of the meat trade, plays an important role in balancing beef supply and demand worldwide. However, research on the evolution of its network patterns remains relatively limited. This article aims to explore the evolution of global beef trade network patterns and provide insights into its implications for sustainable development.MethodsUsing complex network theory, this paper constructs weighted and unweighted global beef trade networks based on international trade data and conducts an in-depth analysis of the evolution of global beef trade patterns from 2013 to 2022 across the overall, individual, and clustering levels.ResultsThe analysis reveals an increasing trend in connectivity, efficiency, and tightness within the global beef trade network. In the unweighted network, the core beef-importing countries are primarily concentrated in Germany, the United Arab Emirates, and the Netherlands. However, in the weighted network, the core importing countries shift to the United States, Japan, and China. Meanwhile, the core beef-exporting countries consistently remain Australia, Brazil, and New Zealand in both network types. Additionally, the analysis identifies clustering and regionalization characteristics within the global beef trade blocks.DiscussionThese findings highlight the evolving dynamics of global beef trade, emphasizing the roles of key countries and the structural shifts in the trade network. The study provides targeted recommendations for promoting sustainable development in the beef trade sector.

Unravelling the landscape of global cobalt trade: Patterns, robustness, and supply chain security

With the development of technology and the widespread adoption of digital technology, the trade volume of electronic products keeps improving. For a country’s trade situation, it is important to study the global trade of electronic products. In this paper, the data on global trade in electronic products from 240–246 countries and regions from 2000 to 2021 are used to create complex network models. Characteristic indicators, such as the network density, average clustering coefficient, average path length, and centrality are used to analyze the evolution of the global electronic product trade network pattern. The results of the complex network analysis show the following: (1) Since 2000, global electronic products have shown a trend of fluctuating growth, showing a state of three-pole differentiation. In addition, the trade volume is unevenly distributed, with the United States and China in the leading positions. (2) The global electronics trade network has significant scale-free and small-world characteristics, with high network density and close ties between countries. (3) There are differences between the closeness centrality and the betweenness centrality of the global electronic product trade network. The core countries are mainly in Europe and North America, while the influence of Asian countries is rising. (4) The global electronic product trade network has a clear division of communities and undergoes dynamic evolution. (5) Global electronic product trade is influenced by natural resources, economic and technological strength, political culture, and other factors. Finally, three policy suggestions are made for the development of China’s electronics trade.

Exploring the complex structural evolution of global primary product trade network

In the context of escalating geopolitical tensions, recurring aircraft safety incidents, and frequent unforeseen events, the security of aircraft supply faces significant challenges. This research employs complex network theory to analyze the evolutionary characteristics of three global aircraft trade network (GATN) systems from 2015 to 2024. It then applies the entropy-weighted TOPSIS method to assess node importance within the network and finally conducts a robustness analysis based on the node importance ranking. The results indicate that the number of participating countries has declined post-pandemic, while trade concentration has increased. Analysis of the node’s importance reveals that the United States holds the most critical role in the GATN. The global medium aircraft trade network is characterized by one dominant player alongside several strong competitors, whereas the global large aircraft trade network features multiple major players coexisting. Regarding network robustness, targeted node attacks cause significantly more disruption than random node attacks. After removing 10% of key nodes, the global small aircraft trade network’s average connectivity fell to 0.6, and efficiency dropped to 0.1. Similar patterns were observed in the medium and large aircraft networks, with connectivity decreasing to 0.4 and efficiency to 0.05. Under targeted attacks, the global small aircraft trade network is more robust than the medium and large ones. This study provides quantitative insights to help optimize aircraft trade strategies.

The food production system is increasingly global and seafood is among the most highly traded commodities. Global trade can improve food security by providing access to a greater variety of foods, increasing wealth, buffering against local supply shocks, and benefit the environment by increasing overall use efficiency for some resources. However, global trade can also expose countries to external supply shocks and degrade the environment by increasing resource demand and loosening feedbacks between consumers and the impacts of food production. As a result, changes in global food trade can have important implications for both food security and the environmental impacts of production. Measurements of globalization and the environmental impacts of food production require data on both total trade and the origin and destination of traded goods (the network structure). While the global trade network of agricultural and livestock products has previously been studied, seafood products have been excluded. This study describes the structure and evolution of the global seafood trade network, including metrics quantifying the globalization of seafood, shifts in bilateral trade flows, changes in centrality and comparisons of seafood to agricultural and industrial trade networks. From 1994 to 2012 the number of countries trading in the network remained relatively constant, while the number of trade partnerships increased by over 65%. Over this same period, the total quantity of seafood traded increased by 58% and the value increased 85% in real terms. These changes signify the increasing globalization of seafood products. Additionally, the trade patterns in the network indicate: increased influence of Thailand and China, strengthened intraregional trade, and increased exports from South America and Asia. In addition to characterizing these network changes, this study identifies data needs in order to connect seafood trade with environmental impacts and food security outcomes.

Understanding the global trade network in the printing industry is crucial for promoting sustainable development and cultural exchange and knowledge dissemination. However, the extant literature does not reveal the contours of the global cultural printed material trade network. This paper uses a social network analysis and QAP analysis to explore the global printing industry trade network pattern. The aim of this paper is to discern the core and emerging nodes and explore the evolutional characteristics on the network spatial linkage and country role. The results show the following: ① The printing industry’s global trade network is growing increasingly intricate, with trade links between nations (regions) becoming closer, the network’s connectivity steadily improving, and the hierarchical structure becoming more apparent. ② Germany, France, and Belgium are important intermediary bridges. The “circle of friends” in the trade of cultural products has a growing effect, and China can more easily establish close ties with Southeast Asia, Northern Europe, and Central and Eastern Europe. ③ The industrial chain and geographical proximity are the primary factors in the formation of the trade network. Economic proximity and political proximity significantly and positively contribute to the formation of the trade network, while institutional stability gradually plays a weaker role. As for cultural proximity, a common language and colonial relationship will positively contribute to the formation of a network, while immigrants have no obvious impact. Digital technology is becoming an “emerging force”. Additionally, this paper extends sustainable policies and recommendations for the global cultural trade.

Global commodity trade networks are critical to our collective sustainable development. Their increasing interconnectedness pose two practical questions: (i) Do the current network configurations support their further growth? (ii) How resilient are these networks to economic shocks? We analyze the data of global commodity trade flows from 1996 to 2012 to evaluate the relationship between structural properties of the global commodity trade networks and (a) their dynamic growth, as well as (b) the resilience of their growth with respect to the 2009 global economic shock. Specifically, we explore the role of network efficiency and redundancy using the information theory-based network flow analysis. We find that, while network efficiency is positively correlated with growth, highly efficient systems appear to be less resilient, losing more and gaining less growth following an economic shock. While all examined networks are rather redundant, we find that network redundancy does not hinder their growth. Moreover, systems exhibiting higher levels of redundancy lose less and gain more growth following an economic shock. We suggest that a strategy to support making global trade networks more efficient via, e.g., preferential trade agreements and higher specialization, can promote their further growth; while a strategy to increase the global trade networks’ redundancy via e.g., more abundant free-trade agreements, can improve their resilience to global economic shocks.

[Purpose] Global economic integration has intensified cereal trade, reshaping China’s grain security. Strengthening China’s role in the global cereal trade network is vital for improving trade patterns and safeguarding food security. [Design] Using bilateral trade data for eight major cereals in over 200 countries (1990–2021), this study applies social network analysis to construct global trade networks, measure key indicators, and visualize structural changes with Gephi. [Findings] From 1990 to 2021, average node degrees rose, with North America, Europe, and Australia as core hubs. Node degrees follow a power-law distribution, network density increased, clustering coefficients remained stable, and path lengths showed an inverted “U” trend. The network is moving toward decentralization and diversification. [Originality] By combining micro-level cereal trade analysis with social network methods, this study depicts the evolution of global trade structures, tracks China’s shifting position, and suggests new directions for national food security.

Existing studies mainly focus on the evolutionary characteristics of the global crude oil trade network under a steady state, neglecting to analyze the competition and cooperation among countries regarding crude oil as a strategic resource from a spatial–geographical perspective. There needs to be more studies analyzing the impact of crude oil trade disruptions on the resilience of the whole network from the perspective of supply and demand shocks in different influential countries, thus promoting the sustainable development of the global economy and the transition to green energy. Based on the global crude oil trade data from 2007 to 2020, this paper examines the structural evolution of the trade network using a complex network approach and simulates the impact of disruptions on its resilience. Results indicate that the global crude oil trade network expands and becomes more closely connected, and five major trade groups have been formed. Further simulation reveals that the impact of national disruptions on global trade resilience is not linear. Moreover, the influence from core countries is significantly higher than peripheral countries.

With the rapid depletion of fossil fuels and increasing concern about climate change, photovoltaic systems have become a key technology option for realizing a decarbonized power sector and sustainable energy supply. The global trade in photovoltaic cells has increased dramatically in the last two decades and deserves a dedicated investigation. First, from a static analysis perspective, this study builds the global photovoltaic cell trade network and trade competition network from 2000 to 2019 and analyzes the trade characteristics and competition pattern in the global photovoltaic cell trade. Second, from a dynamic analysis perspective, the potential impacts of coronavirus disease 2019 on the global photovoltaic cell trade is simulated based on 2019 trade data. The network analyses show that China, Germany and Japan have long dominated the trade market in photovoltaic cells. From 2000 to 2019, China’s total imports and exports were the largest. Asian countries held an important position in global photovoltaic cell exports. The competition in the global photovoltaic cell trade was concentrated in Asia and Europe. The simulation results indicate that the global photovoltaic cell trade network shows a “robust-yet-fragile” configuration. This network is more resistant to demand-reduction-driven shocks than to supply-reduction-driven shocks. Policy implications are provided for managing the photovoltaic cell trade at the national and global levels and coping with future extreme disturbances.

Evolution of the global coal trade network: A complex network analysis

With the global spread of environmental protection, green trade has become a new trend in trade development. Based on the total import and export value of green products from 227 countries (regions) from 2012 to 2020, this study uses a complex network analysis method to construct a global green trade network, study the structural characteristics and evolution of the network from three dimensions–whole, community, and node–and analyze the influence mechanism of the global green trade network using an exponential random graph model. The estimation results of the exponential random graph model show that the economic size gap, population size gap, development level, trade liberalization and language differences between countries will affect the formation of the global green trade network. The global green trade network has strong mutuality, and it is easier for countries with large differences in economic scale, countries with the same WTO member and developed countries to establish green trade relations. The common language network has a positive impact on the global green trade network. Countries should be clear about their own characteristics and position in the global green trade network, and actively develop green trade.

Identification of global oil trade patterns: An empirical research based on complex network theory