IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i4p1728-d1063039.html
   My bibliography  Save this article

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

Author

Listed:
  • Xiaoyu Niu

    (School of Geography Science, Nanjing Normal University, Nanjing 210023, China)

  • Wei Chen

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Nyuying Wang

    (China Centre for Urban Development, Beijing 100038, China)

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.

Suggested Citation

  • Xiaoyu Niu & Wei Chen & Nyuying Wang, 2023. "Spatiotemporal Dynamics and Topological Evolution of the Global Crude Oil Trade Network," Energies, MDPI, vol. 16(4), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1728-:d:1063039
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/4/1728/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/4/1728/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wu, X.F. & Chen, G.Q., 2019. "Global overview of crude oil use: From source to sink through inter-regional trade," Energy Policy, Elsevier, vol. 128(C), pages 476-486.
    2. Wu, Gang & Pu, Yue & Shu, Tianran, 2021. "Features and evolution of global energy trade network based on domestic value-added decomposition of export," Energy, Elsevier, vol. 228(C).
    3. Wei Chen & Hang-Hyun Jo, 2021. "Delineating the Spatial Boundaries of Megaregions in China: A City Network Perspective," Complexity, Hindawi, vol. 2021, pages 1-10, December.
    4. Sofia Berdysheva & Svetlana Ikonnikova, 2021. "The Energy Transition and Shifts in Fossil Fuel Use: The Study of International Energy Trade and Energy Security Dynamics," Energies, MDPI, vol. 14(17), pages 1-26, August.
    5. Al Rousan, Sahel & Sbia, Rashid & Tas, Bedri Kamil Onur, 2018. "A dynamic network analysis of the world oil market: Analysis of OPEC and non-OPEC members," Energy Economics, Elsevier, vol. 75(C), pages 28-41.
    6. Song, Zhouying & Zhu, Qiaoling & Han, Mengyao, 2021. "Tele-connection of global crude oil network: Comparisons between direct trade and embodied flows," Energy, Elsevier, vol. 217(C).
    7. Fen Li & Cunyi Yang & Zhenghui Li & Pierre Failler, 2021. "Does Geopolitics Have an Impact on Energy Trade? Empirical Research on Emerging Countries," Sustainability, MDPI, vol. 13(9), pages 1-24, May.
    8. Hao, Xiaoqing & An, Haizhong & Qi, Hai & Gao, Xiangyun, 2016. "Evolution of the exergy flow network embodied in the global fossil energy trade: Based on complex network," Applied Energy, Elsevier, vol. 162(C), pages 1515-1522.
    9. Xiaoyong Xiao & Jing Huang, 2018. "Dynamic Connectedness of International Crude Oil Prices: The Diebold–Yilmaz Approach," Sustainability, MDPI, vol. 10(9), pages 1-16, September.
    10. An, Haizhong & Zhong, Weiqiong & Chen, Yurong & Li, Huajiao & Gao, Xiangyun, 2014. "Features and evolution of international crude oil trade relationships: A trading-based network analysis," Energy, Elsevier, vol. 74(C), pages 254-259.
    11. Ge, Jianping & Wang, Xibo & Guan, Qing & Li, Weiheng & Zhu, He & Yao, Min, 2016. "World rare earths trade network: Patterns, relations and role characteristics," Resources Policy, Elsevier, vol. 50(C), pages 119-130.
    12. Guo, Yue & Yang, Yu & Wang, Chang, 2021. "Global energy networks: Geographies of mergers and acquisitions of worldwide oil companies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    13. Reboredo, Juan C., 2011. "How do crude oil prices co-move?: A copula approach," Energy Economics, Elsevier, vol. 33(5), pages 948-955, September.
    14. Charalampos Basdekis & Apostolos Christopoulos & Ioannis Katsampoxakis & Vasileios Nastas, 2022. "The Impact of the Ukrainian War on Stock and Energy Markets: A Wavelet Coherence Analysis," Energies, MDPI, vol. 15(21), pages 1-15, November.
    15. Ho, Anson T.Y. & Huynh, Kim P. & Jacho-Chávez, David T., 2019. "Using nonparametric copulas to measure crude oil price co-movements," Energy Economics, Elsevier, vol. 82(C), pages 211-223.
    16. Zhang, Hai-Ying & Ji, Qiang & Fan, Ying, 2014. "Competition, transmission and pattern evolution: A network analysis of global oil trade," Energy Policy, Elsevier, vol. 73(C), pages 312-322.
    17. Xi, Xian & Zhou, Jinsheng & Gao, Xiangyun & Liu, Donghui & Zheng, Huiling & Sun, Qingru, 2019. "Impact of changes in crude oil trade network patterns on national economy," Energy Economics, Elsevier, vol. 84(C).
    18. Jan Bentzen, 2007. "Does OPEC influence crude oil prices? Testing for co-movements and causality between regional crude oil prices," Applied Economics, Taylor & Francis Journals, vol. 39(11), pages 1375-1385.
    19. Jia, Xiaoliang & An, Haizhong & Sun, Xiaoqi & Huang, Xuan & Wang, Lijun, 2017. "Evolution of world crude oil market integration and diversification: A wavelet-based complex network perspective," Applied Energy, Elsevier, vol. 185(P2), pages 1788-1798.
    20. Yang, Yu & Poon, Jessie P.H. & Liu, Yi & Bagchi-Sen, Sharmistha, 2015. "Small and flat worlds: A complex network analysis of international trade in crude oil," Energy, Elsevier, vol. 93(P1), pages 534-543.
    21. Ji, Qiang & Zhang, Hai-Ying & Zhang, Dayong, 2019. "The impact of OPEC on East Asian oil import security: A multidimensional analysis," Energy Policy, Elsevier, vol. 126(C), pages 99-107.
    22. Du, Ruijin & Wang, Ya & Dong, Gaogao & Tian, Lixin & Liu, Yixiao & Wang, Minggang & Fang, Guochang, 2017. "A complex network perspective on interrelations and evolution features of international oil trade, 2002–2013," Applied Energy, Elsevier, vol. 196(C), pages 142-151.
    23. Zhang, Hai-Ying & Ji, Qiang & Fan, Ying, 2015. "What drives the formation of global oil trade patterns?," Energy Economics, Elsevier, vol. 49(C), pages 639-648.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zeyu Hou & Xiaoyu Niu & Zhaoyuan Yu & Wei Chen, 2023. "Spatiotemporal Evolution and Market Dynamics of the International Liquefied Natural Gas Trade: A Multilevel Network Analysis," Energies, MDPI, vol. 17(1), pages 1-16, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xi, Xian & Zhou, Jinsheng & Gao, Xiangyun & Liu, Donghui & Zheng, Huiling & Sun, Qingru, 2019. "Impact of changes in crude oil trade network patterns on national economy," Energy Economics, Elsevier, vol. 84(C).
    2. N. Wei & W. -J. Xie & W. -X. Zhou, 2021. "Robustness of the international oil trade network under targeted attacks to economies," Papers 2101.10679, arXiv.org, revised Jan 2021.
    3. Zhang, Hongwei & Wang, Ying & Yang, Cai & Guo, Yaoqi, 2021. "The impact of country risk on energy trade patterns based on complex network and panel regression analyses," Energy, Elsevier, vol. 222(C).
    4. Zhang, Jing, 2019. "Oil and gas trade between China and countries and regions along the ‘Belt and Road’: A panoramic perspective," Energy Policy, Elsevier, vol. 129(C), pages 1111-1120.
    5. Wang, Wenya & Fan, L.W. & Zhou, P., 2022. "Evolution of global fossil fuel trade dependencies," Energy, Elsevier, vol. 238(PC).
    6. Song, Zhouying & Zhu, Qiaoling & Han, Mengyao, 2021. "Tele-connection of global crude oil network: Comparisons between direct trade and embodied flows," Energy, Elsevier, vol. 217(C).
    7. Xuanru Zhou & Hua Zhang & Shuxian Zheng & Wanli Xing & Pei Zhao & Haiying Li, 2022. "The Crude Oil International Trade Competition Networks: Evolution Trends and Estimating Potential Competition Links," Energies, MDPI, vol. 15(7), pages 1-20, March.
    8. Wei, Na & Xie, Wen-Jie & Zhou, Wei-Xing, 2022. "Robustness of the international oil trade network under targeted attacks to economies," Energy, Elsevier, vol. 251(C).
    9. Zhang, Hongwei & Wang, Ying & Zhu, Xuehong & Guo, Yaoqi, 2020. "The impact of energy trade patterns on CO2 emissions: An emergy and network analysis," Energy Economics, Elsevier, vol. 92(C).
    10. Xie, Wen-Jie & Wei, Na & Zhou, Wei-Xing, 2023. "An interpretable machine-learned model for international oil trade network," Resources Policy, Elsevier, vol. 82(C).
    11. Huan Chen & Lixin Tian & Minggang Wang & Zaili Zhen, 2017. "Analysis of the Dynamic Evolutionary Behavior of American Heating Oil Spot and Futures Price Fluctuation Networks," Sustainability, MDPI, vol. 9(4), pages 1-29, April.
    12. Cappelli, Federica & Carnazza, Giovanni & Vellucci, Pierluigi, 2023. "Crude oil, international trade and political stability: Do network relations matter?," Energy Policy, Elsevier, vol. 176(C).
    13. Liu, Litao & Cao, Zhi & Liu, Xiaojie & Shi, Lei & Cheng, Shengkui & Liu, Gang, 2020. "Oil security revisited: An assessment based on complex network analysis," Energy, Elsevier, vol. 194(C).
    14. Li, Xiaotong & Zhang, Hua & Zhou, Xuanru & Zhong, Weiqiong, 2022. "Research on the evolution of the global import and export competition network of chromium resources from the perspective of the whole industrial chain," Resources Policy, Elsevier, vol. 79(C).
    15. Han, Mengyao & Xiong, Jiao & Yang, Yu, 2023. "Comparisons between direct and embodied natural gas networks: Topology, dependency and vulnerability," Energy, Elsevier, vol. 280(C).
    16. Wang, Wenya & Fan, Liwei & Li, Zhenfu & Zhou, Peng & Chen, Xue, 2021. "Measuring dynamic competitive relationship and intensity among the global coal importing trade," Applied Energy, Elsevier, vol. 303(C).
    17. Guo, Yue & Yang, Yu & Wang, Chang, 2021. "Global energy networks: Geographies of mergers and acquisitions of worldwide oil companies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    18. Yan, Zhaojin & Xiao, Yijia & Cheng, Liang & Chen, Song & Zhou, Xiao & Ruan, Xiaoguang & Li, Manchun & He, Rong & Ran, Bin, 2020. "Analysis of global marine oil trade based on automatic identification system (AIS) data," Journal of Transport Geography, Elsevier, vol. 83(C).
    19. Shao, Yanmin & Qiao, Han & Wang, Shouyang, 2017. "What determines China's crude oil importing trade patterns? Empirical evidences from 55 countries between 1992 and 2015," Energy Policy, Elsevier, vol. 109(C), pages 854-862.
    20. Zhu, Zhiyun & Dong, Zhiliang & Zhang, Yanxing & Suo, Guibin & Liu, Sen, 2020. "Strategic mineral resource competition: Strategies of the dominator and nondominator," Resources Policy, Elsevier, vol. 69(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1728-:d:1063039. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.