Bargaining in endogenous trading networks

Growing global supply chain uncertainties significantly threaten China’s forage import security. The evolving characteristics of the global forage trade network directly impact the stability of China’s supply. This study constructs a directed, weighted trade network based on global forage products trade data (2000–2024). Using complex network analysis methods, it systematically analyzes the network’s topological structure and evolutionary patterns, with a focus on their impact on China’s import security. The study addresses the following questions: What evolutionary patterns does the global forage trade network exhibit in terms of its topological structure? How does the evolution of this network impact the import security of forage products in China, specifically regarding supply chain stability and risk resilience? The research findings indicate the following: (1) From 2000 to 2024, the total volume of global forage products trade increased by 48.17%, primarily driven by forage products excluding alfalfa meal and pellets, which accounted for an average of 82.04% of volume annually. Additionally, the number of participating countries grew by 21.95%. (2) The global forage products trade network follows a power–law distribution, characterized by increasing network density, a clustering coefficient that initially declines and then rises, and a shortening of the average path length. (3) The core structure of the global forage products trade network shows an evolutionary trend of diffusion from core nodes in North America, Oceania, and Asia to multiple core nodes, including those in North America, Oceania, Europe, Africa, and Asia. (4) China’s forage products trade network displays distinct phase characteristics; however, imports face significant risks from high supply chain dependency and exposure to international price fluctuations. Based on these conclusions, it is recommended that China actively expands trade relations with potential product-exporting countries in Africa, encouraging enterprises to “go global.” Additionally, China should establish a three-dimensional supply chain security system, comprising maritime, land, and storage components, to enhance risk resistance and import safety.

Purpose This study aims to analyze a trade network between countries on agricultural products exports and imports from a social network perspective, and specifically identify the core and peripheral countries of agricultural product trade network. Design/Methodology/Approach We calculate coreness score and core-peripheral matrix values using core-periphery structure analysis of social network analysis techniques and recommend core countries and periphery countries. Findings We identified countries belonging to each block of the core-periphery structure, namely core block, peripheral block, core-peripheral block, and peripheral-core block, to discover the path and impact of crisis movement. Research Implications This study made it possible to predict how to respond to a crisis in the trade network from a macroscopic point of view to managers of a country or a company. The research implications of this study increased the understanding of core-peripheral structure analysis through network visualization as well as mathematical calculations.

Bilateral oligopoly — The efficiency of intermediate goods markets

With origins in post-war development thinking, the core–periphery concept has spread across the social and, increasingly, the natural sciences. Initially reflecting divergent socioeconomic properties of geographical regions, its relational connotations rapidly led to more topological interpretations. In today's network science, the standard core–periphery model consists of a cohesive set of core actors and a peripheral set of internally disconnected actors. Exploring the classical core–periphery literature, this paper finds conceptual support for the characteristic intra-categorical density differential. However, this literature also lends support to the notions of peripheral dependency and core dominance, power-relational aspects that existing approaches do not capture. To capture such power-relations, this paper suggests extensions to the correlation-based core–periphery metric of Borgatti and Everett (2000). Capturing peripheral dependency and, optionally, core dominance, these extensions allow for either measuring the degree of such power-relational features in given core–periphery partitions, or as part of a criteria function to search for power-relational core–periphery structures. Applied to the binary and valued citation data in Borgatti and Everett (2000), the proposed extensions seemingly capture dependency and dominance features of core–periphery structures. This is particularly evident when, circling back to the original domains of the concept, examining the network of European commodity trade in 2010.

An accessibility graph of a network contains a link wherever there is a path of arbitrary length between two nodes. We generalize the concept of accessibility to temporal networks. Building an accessibility graph by consecutively adding paths of growing length (unfolding), we obtain information about the distribution of shortest path durations and characteristic time scales in temporal networks. Moreover, we define causal fidelity to measure the goodness of their static representation. The practicability of our proposed methods is demonstrated for three examples: networks of social contacts, livestock trade, and sexual contacts.

Can collapsing business networks explain economic downturns?

As a critical raw material in the semiconductor and new energy sectors, antimony is a strategic mineral resource for nations to safeguard industrial chain security. However, the scarcity of its resources and the complexity of its trade pattern underscore the urgency of antimony-related research. This study aims to reveal the structural characteristics of the global antimony trade network and explore the external factors influencing trade. Based on global antimony trade data from 2007 to 2022, the characteristics of the antimony trade network were analyzed using the complex network analysis method, and the influencing factors of antimony trade were examined via the fixed effects model. The results show that the global antimony trade network maintains a density of 0.05–0.06, with an average path length of 2.4–2.7 and a network diameter that mainly fluctuates between 5 and 6. The average clustering coefficient fluctuates within the range of 0.35–0.45. Overall, the network exhibits the characteristics of stable transmission efficiency, loose overall connectivity, and local agglomeration without a consistent upward or downward trend. Countries such as Germany, China, and the United States occupy core positions in the network. The fixed effects model indicates that GDP and LOGISTICS development are key factors promoting trade, while TARIFFS and REGULATORY policies have a significant inhibitory effect on trade. Therefore, ① Focus on the High-End Development of the Antimony Industry Chain and Promote the In-Depth Integration of Antimony Trade with the Semiconductor and New Energy Industries; ② Improve the Cross-Border Logistics and Warehousing System for Antimony Trade to Ensure the Efficient Circulation of Strategic Resources; ③ Promote; Promote Tariff Liberalization in Antimony Trade and Eliminate Market Access Barriers; ④ Strengthen the Government’s Strategic Support for the Antimony Industry to Enhance Global Discourse Power in Antimony Trade; Trade; ⑤ Maintain Macroeconomic Stability and Flexibly Manage Exchange Rates to Safeguard the Resilience of Antimony Trade.

Comparison of weighted and unweighted network analysis in the case of a pig trade network in Northern Germany

Global supply chains face increasing vulnerability to disruptions from geopolitical tensions, natural disasters, and demand shocks. The global trade network for railway vans, critical for transcontinental freight transport, remains understudied despite its foundational role in global logistics. This study addresses the gap in understanding how the railway vans trade network structure evolves and responds to different types of shocks, moving beyond static analyses to capture dynamic vulnerabilities. Using UN Comtrade data (2013-2024), multi-level network analysis examined structural evolution at macroscopic, mesoscopic, and microscopic scales. Three risk propagation models simulated supply disruption, demand shock, and cooperation disruption scenarios to assess systemic vulnerabilities. The network transformed from a polycentric to core-periphery structure, with China dominating exports (67 partners in 2024) and Germany leading European integration. Supply disruptions from Romania and Czechia affected up to 114 countries under low risk absorption capacity (α = 0.1), while demand shocks from the USA impacted 53 countries. The disruption of strategic trade links, such as China-Australia, triggered severe systemic risks. The systemic criticality of risk sources varies by shock type, requiring context-specific resilience strategies. The findings guide policymakers in identifying critical vulnerabilities and designing targeted interventions for enhancing supply chain resilience in infrastructure sectors.

Trade and Domestic Production Networks

Financial networks, bank efficiency and risk-taking

Core-Periphery Trading Networks

A novel approach for analyzing the structural integrity and operational vulnerability of complex networks using intuitionistic fuzzy graphs has been modeled. While traditional fuzzy graph metrics focus primarily on existence, they fail to capture the holistic systemic impact of failures. To overcome this limitation, a scalar-based measure of nodal importance that integrates both existence (membership degree) and non-existence (non-membership degree) values of incident edges into a single critical metric has been developed. The proposed indices demonstrate enhanced sensitivity to network perturbations compared to conventional degree centrality measures, capturing latent vulnerabilities in critical infrastructure topologies. Based on this, two indices are proposed: Intuitionistic Fuzzy Degree Index and Intuitionistic Edge Interaction Index. These indices quantify the total system activity, stress dispersion, overall network cohesiveness, and potential for cascading failure propagation. When applied to synthetic core-periphery networks, the proposed indices identified critical nodes with superior discrimination capability compared to existing fuzzy graph metrics, revealing that removal of identified nodes results in system-wide connectivity degradation observable through both membership and non-membership approximations. This methodology was applied to a core-periphery communication network to analyze the systemic consequences of node removal. Experimental validation on networks of varying sizes demonstrates that the Intuitionistic Edge Interaction Index achieves robust node criticality ranking across heterogeneous network topologies with improved predictive accuracy for cascade initiation points. This work provides network analysts and engineers a quantitative tool to precisely assess criticality and inform targeted resilience strategies in uncertain, high-risk environments.

This paper presents a network-based framework for evaluating collaborative collision-avoidance strategies in heterogeneous mobile agent systems. By modeling interactions among both automated and human-operated platforms as complex random networks, the approach quantifies coordination effectiveness through structural metrics such as average path length, clustering coefficient, and betweenness centrality. These measures assess communication efficiency, local cohesion, and network robustness under dynamic, high-density conditions. The framework supports systematic simulation and analysis of multi-agent behaviors, offering a scalable tool for optimizing coordinated navigation in intelligent transportation environments.

Relationships in the interbank market