Spatiotemporal Dynamics and Topological Evolution of the Global Crude Oil Trade Network

Abstract

The high separation of crude oil supply and demand markets has led to the formation of a global crude oil trading system. This paper constructs global crude oil trade networks, integrates macro, meso, and micro network analysis methods, combines geospatial visualization techniques, and then portrays the spatiotemporal patterns and topological evolution of the global crude oil trade networks. Thus, it attempts to dig deeper into the world crude oil competition and cooperation links and evolution laws and provides a scientific reference for a comprehensive understanding of the global crude oil market dynamics. The results show that: (1) After three fluctuations of increase and decrease since 2000, the global crude oil trade volume is entering the adjustment period, and the scale of the crude oil market is rising slowly. (2) The international crude oil trade has formed trade network patterns with complex structures, clear hierarchy and unbalanced distribution. The “rich club” phenomenon is significant, with large trading countries dominating the trade network. (3) The scale and density of the global crude oil trade network show a trend of increasing and then decreasing, the network agglomeration pattern becoming more obvious, the inter-nodal links continuously strengthening, and the network connectivity improving. (4) The global crude oil trade networks are characterized by core–periphery structures, and the polarization effect is significant. The US, Russia, China, Japan, the Netherlands, and South Korea hold the core positions in the crude oil trade network, and the major importing countries have become the dominant forces in the trade network. In addition, we present policy suggestions for different types of countries for energy transformation and security in the global trade market system, which can be used as a reference for policymakers.

Spatiotemporal Evolution and Market Dynamics of the International Liquefied Natural Gas Trade: A Multilevel Network Analysis

“…Li et al investigated the evolution characteristics of the natural gas trade network along the "Belt and Road" (BRI) by using the network indicators and showed that there is an increasingly significant polarization effect in the BRI LNG trade network, and that the level of market monopoly is increasing [21]. Subsequently, scholars are no longer limited to a single portrayal of the overall LNG trade network, and network analysis methods such as community detection [22,23], core-periphery division [24,25], and link prediction [26] have also been used to explore the topological structure [27], the market competition pattern [28], and the prediction of the potential trade relations [29] of the LNG trade network, to deeply explore the pattern evolution of the trade network. Filimonova et al constructed directed network diagrams of the LNG trade, where the global LNG trade network was divided into six subgroups, with Qatar having the richest potential links [27].…”

Understanding Global Rice Trade Flows: Network Evolution and Implications

“…Therefore, how to accurately identify the changes in global rice production and consumption patterns from the network perspective is not only conducive to comprehensively revealing the evolution laws of the global rice-trade flows, but also an objective need to safeguard global food security and the stability of rice supply under the complex international situation. Accompanied by the rise in network science, the complex network analysis method can quantitatively assess the trade links between countries [15,16], which provides cutting-edge analytical approaches for exploring global-trade patterns and development trends. In this context, academics have gradually begun to draw on complex network analysis to analyze the patterns and evolution of the global food trade from a network perspective, with research topics focusing on the pattern evolution of the food-trade network [17,18], the differences in the trade patterns of different crops [19], and the vulnerability and risk in food trade and supply [20][21][22].…”

Evolution of “the Belt and Road” trade network connectivity

“…等环节视角， 探究不同分工模式对国际贸易带来的 影响和机制 [15][16][17] 。长期以来， 经济地理学对国际贸 易研究相对零散， 主要侧重于国际贸易地理结构的 描述 [12,[18][19] 。而随着全球价值链深入发展， 国际贸易 趋向网络化发展， 最终构成了世界贸易网络体系。 国家与国家间在空间上形成的相互联系的贸易流， 交织构成了国际贸易网络结构。在此背景下， 贸易 网络研究逐步成为透视国际贸易体系的重要路 径。当前， 针对贸易网络的研究大体可以分为 3 类。第一类， 从网络宏观特征出发， 学者们利用网 络密度、 集聚系数、 平均最短路径等指标对网络拓 扑结构进行刻画和分析 [20] ， 研究发现， 世界贸易网 络同样具有小世界特性 [21] 、 幂律分布 [22] 、 社区结构 [23] 等典型的复杂网络特征。第二类， 从网络微观尺度 出发， 部分研究侧重于运用网络中心性等指标， 考 察贸易网络中不同国家在网络中的地位或角色变 化， 分析网络的等级结构特征 [24][25] 。第三类， 聚焦于 网络中观尺度特征， 学者们利用社区发现 [26][27] 、 核心 -边缘结构 [28] 、 块模型 [29] 等分析方法， 探究贸易网络 的结构特征及其与整体贸易网络的嵌套关系。总 体上， 当前国际贸易网络研究取得了明显进展， 有 力深化了关于国际贸易网络发展的科学认知。特 别是当前网络分析方法发展迅猛， 为各领域提供了 大量具有洞察力的网络分析手段， 被越来越多地应 用到国际贸易等研究领域中， 并展现出明显的学科 交叉特性。 随着 "一带一路" 倡议深入发展， 学术界对 "一 带一路" 贸易网络研究也逐渐升温， 越来越多的学 者借助网络分析方法探究 "一带一路" 沿线国家间 贸易联系构成的复杂网络。邹嘉龄等 [30] 利用社会 网络分析方法刻画了 "一带一路" 沿线国家贸易网 络基本特征与组团结构， 并进一步分析了中国等区 域贸易网络的 "核心-边缘" 结构。为探究不同产 品在 "一带一路" 贸易网络结构特征和影响因素， 部 分学者对能源 [31] 、 农产品 [32] 、 技术 [33] 等分行业贸易网 络展开了相关研究。其中， 宋周莺等 [34] 基于社区发 现算法， 对 "一带一路" 贸易网络与全球贸易网络的 拓扑特征进行了分析， 发现 "一带一路" 区域联系强 度具有差异性。李优树等 [35] 从产业链视角分别构 建了 4 类 "一带一路" 沿线国家石油产业链贸易网 络， 得出该贸易网络整体密度逐渐增大， 贸易联系 愈加紧密， 且具有 "小世界性" 特征的结论。杨文龙 等 [21] 借用引力模型对 "一带一路" 贸易网络进行了 作为国际经济合作平台， "一带一路" 倡议没有 限定具体的空间范围。考虑到研究的一致性与合 理性， 参考现有研究基础 [3,[36][37]…”