IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v74y2021ics0301420721003652.html
   My bibliography  Save this article

Lithium resource allocation optimization of the lithium trading network based on material flow

Author

Listed:
  • Yang, Ping
  • Gao, Xiangyun
  • Zhao, Yiran
  • Jia, Nanfei
  • Dong, Xiaojuan

Abstract

The global consumption of electronic products and new energy vehicles is continually increasing, driving the rapid development of lithium resources and the associated industrial chain. The unbalanced distribution of global lithium resources requires trade among various countries to meet their resource needs. Transaction relationships among countries result in unequal transportation distances and varied transportation costs. An unreasonable transaction relationship will increase transportation costs and the risk of industrial chain fractures, whereas a reasonable transaction relationship can reduce transportation costs and shorten the supply distance of the industrial chain. Based on the material flow analysis method and complex network theory, this paper analyzed lithium transactions. Then, an optimization model was designed to minimize transportation costs. Finally, the solution of the model was presented by the table on the operating method. The research results show that a mismatch between the transaction volume and the number of transaction relationships in lithium trading increased lithium transaction costs. Through optimization, the total transportation costs became significantly lower. Participating countries autonomously chose nearby partners with rich lithium batteries and related chemicals. Although a few countries paid the price of increasing costs, the optimization process significantly reduced the total costs and achieved the goal of overall optimization. In addition, the lithium trading network identified import and export centers in various regions, such as Argentina, Chile and Bolivia, which form the famous “lithium triangle” in South America. These regions have the potential to develop a complete industrial chain and reduce the risk of industrial chain rupture.

Suggested Citation

  • Yang, Ping & Gao, Xiangyun & Zhao, Yiran & Jia, Nanfei & Dong, Xiaojuan, 2021. "Lithium resource allocation optimization of the lithium trading network based on material flow," Resources Policy, Elsevier, vol. 74(C).
  • Handle: RePEc:eee:jrpoli:v:74:y:2021:i:c:s0301420721003652
    DOI: 10.1016/j.resourpol.2021.102356
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420721003652
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.resourpol.2021.102356?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Li, Tianjiao & Wang, Anjian & Xing, Wanli & Li, Ying & Zhou, Yanjing, 2019. "Assessing mineral extraction and trade in China from 1992 to 2015: A comparison of material flow analysis and exergoecological approach," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    2. 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.
    3. Fernando Moreno-Brieva & Carlos Merino, 2020. "African international trade in the global value chain of lithium batteries," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(6), pages 1031-1052, August.
    4. Swenseth, Scott R. & Godfrey, Michael R., 2002. "Incorporating transportation costs into inventory replenishment decisions," International Journal of Production Economics, Elsevier, vol. 77(2), pages 113-130, May.
    5. Tong, Xin & Lifset, Reid, 2007. "International copper flow network: A blockmodel analysis," Ecological Economics, Elsevier, vol. 61(2-3), pages 345-354, March.
    6. Wang, Peng & Jiang, Zeyi & Geng, Xinyi & Hao, Shiyu & Zhang, Xinxin, 2014. "Quantification of Chinese steel cycle flow: Historical status and future options," Resources, Conservation & Recycling, Elsevier, vol. 87(C), pages 191-199.
    7. Fujino, Toru & Chen, Yu, 2020. "Effects of network structure on the performance of a modeled traffic network under drivers’ bounded rationality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    8. Gong, Hao & Guo, Chunxiang & Liu, Yu, 2021. "Measuring network rationality and simulating information diffusion based on network structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
    9. Zhong, Weiqiong & An, Haizhong & Gao, Xiangyun & Sun, Xiaoqi, 2014. "The evolution of communities in the international oil trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 42-52.
    10. Sun, Xin & Hao, Han & Zhao, Fuquan & Liu, Zongwei, 2017. "Tracing global lithium flow: A trade-linked material flow analysis," Resources, Conservation & Recycling, Elsevier, vol. 124(C), pages 50-61.
    11. Zhong, Weiqiong & An, Haizhong & Fang, Wei & Gao, Xiangyun & Dong, Di, 2016. "Features and evolution of international fossil fuel trade network based on value of emergy," Applied Energy, Elsevier, vol. 165(C), pages 868-877.
    12. Hao, Han & Liu, Zongwei & Zhao, Fuquan & Geng, Yong & Sarkis, Joseph, 2017. "Material flow analysis of lithium in China," Resources Policy, Elsevier, vol. 51(C), pages 100-106.
    13. Chen, Guang & Kong, Rui & Wang, Yixin, 2020. "Research on the evolution of lithium trade communities based on the complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    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. Chen, Jinyu & Luo, Qian & Sun, Xin & Zhang, Zitao & Dong, Xuesong, 2023. "The impact of renewable energy consumption on lithium trade patterns: An industrial chain perspective," Resources Policy, Elsevier, vol. 85(PA).
    2. Hao, Hongchang & Ma, Zhe & Wang, Anjian & Xing, Wanli & Song, Hao & Zhao, Pei & Wei, Jiangqiao & Zheng, Shuxian, 2023. "Modeling and assessing the robustness of the lithium global trade system against cascading failures," Resources Policy, Elsevier, vol. 85(PB).
    3. Zhu, Xuehong & Ding, Qian & Chen, Jinyu, 2022. "How does critical mineral trade pattern affect renewable energy development? The mediating role of renewable energy technological progress," Energy Economics, Elsevier, vol. 112(C).
    4. Fuentealba, Diego & Flores-Fernández, Cherie & Troncoso, Elizabeth & Estay, Humberto, 2023. "Technological tendencies for lithium production from salt lake brines: Progress and research gaps to move towards more sustainable processes," Resources Policy, Elsevier, vol. 83(C).

    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. Jiang, Meihui & An, Haizhong & Guan, Qing & Sun, Xiaoqi, 2018. "Global embodied mineral flow between industrial sectors: A network perspective," Resources Policy, Elsevier, vol. 58(C), pages 192-201.
    2. 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).
    3. Tian, Xu & Geng, Yong & Sarkis, Joseph & Gao, Cuixia & Sun, Xin & Micic, Tatyana & Hao, Han & Wang, Xin, 2021. "Features of critical resource trade networks of lithium-ion batteries," Resources Policy, Elsevier, vol. 73(C).
    4. 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).
    5. Wang, Wenya & Fan, L.W. & Zhou, P., 2022. "Evolution of global fossil fuel trade dependencies," Energy, Elsevier, vol. 238(PC).
    6. Mu, Dong & Ren, Huanyu & Wang, Chao & Yue, Xiongping & Du, Jianbang & Ghadimi, Pezhman, 2023. "Structural characteristics and disruption ripple effect in a meso-level electric vehicle Lithium-ion battery supply chain network," Resources Policy, Elsevier, vol. 80(C).
    7. Hu, Xiaoqian & Wang, Chao & Lim, Ming K. & Chen, Wei-Qiang & Teng, Limin & Wang, Peng & Wang, Heming & Zhang, Chao & Yao, Cuiyou & Ghadimi, Pezhman, 2023. "Critical systemic risk sources in global lithium-ion battery supply networks: Static and dynamic network perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    8. Chen, Jinyu & Luo, Qian & Sun, Xin & Zhang, Zitao & Dong, Xuesong, 2023. "The impact of renewable energy consumption on lithium trade patterns: An industrial chain perspective," Resources Policy, Elsevier, vol. 85(PA).
    9. Hao, Hongchang & Xing, Wanli & Wang, Anjian & Song, Hao & Han, Yawen & Zhao, Pei & Xie, Ziqi & Chen, Xuemei, 2022. "Multi-layer networks research on analyzing supply risk transmission of lithium industry chain," Resources Policy, Elsevier, vol. 79(C).
    10. Cai, Xiaomei & Liu, Chan & Zheng, Shuxian & Hu, Han & Tan, Zhanglu, 2023. "Analysis on the evolution characteristics of barite international trade pattern based on complex networks," Resources Policy, Elsevier, vol. 83(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. Ashfaq, Saleha & Tang, Yong & Maqbool, Rashid, 2020. "Dynamics of spillover network among oil and leading Asian oil trading countries’ stock markets," Energy, Elsevier, vol. 207(C).
    13. Yu, Yu & Ma, Daipeng & Zhu, Weiwei, 2023. "Resilience assessment of international cobalt trade network," Resources Policy, Elsevier, vol. 83(C).
    14. 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).
    15. Wang, Minggang & Chen, Ying & Tian, Lixin & Jiang, Shumin & Tian, Zihao & Du, Ruijin, 2016. "Fluctuation behavior analysis of international crude oil and gasoline price based on complex network perspective," Applied Energy, Elsevier, vol. 175(C), pages 109-127.
    16. Chen, B. & Li, J.S. & Wu, X.F. & Han, M.Y. & Zeng, L. & Li, Z. & Chen, G.Q., 2018. "Global energy flows embodied in international trade: A combination of environmentally extended input–output analysis and complex network analysis," Applied Energy, Elsevier, vol. 210(C), pages 98-107.
    17. Yue, Qiang & Chai, Xicui & Zhao, Feng & He, Junhao & Li, Yun & Wang, Heming, 2023. "Analysis of iron in-use stocks: Evidence from the provincial and municipal levels in China," Resources Policy, Elsevier, vol. 80(C).
    18. Zhiyong Zhou & Jianhui Huang & Ming Li & Yao Lu, 2022. "The Dynamic Evolution of the Material Flow of Lithium Resources in China," Sustainability, MDPI, vol. 14(24), pages 1-19, December.
    19. Kang, Xinyu & Wang, Minxi & Wang, Taixin & Luo, Fanjie & Lin, Jing & Li, Xin, 2022. "Trade trends and competition intensity of international copper flow based on complex network: From the perspective of industry chain," Resources Policy, Elsevier, vol. 79(C).
    20. Elisa Alonso & David Pineault & Nedal T. Nassar, 2023. "Streamlined approach for assessing embedded consumption of lithium and cobalt in the United States," Journal of Industrial Ecology, Yale University, vol. 27(1), pages 33-42, February.

    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:eee:jrpoli:v:74:y:2021:i:c:s0301420721003652. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    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.