IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v276y2023ics0360544223009155.html
   My bibliography  Save this article

How to facilitate efficient blue carbon trading? A simulation study using the game theory to find the optimal strategy for each participant

Author

Listed:
  • He, Yixiong
  • Zhang, Fengxuan
  • Wang, Yanwei

Abstract

Blue carbon trading provides not only an extra impetus to the diversification of the carbon trading system, but also substantial support for achieving the net-zero greenhouse gas emission target. Being aware of its importance, this study strives to lay a theoretical foundation for it and help blue carbon fully realize its value. While staying realistic and considering the complex relationship among the relevant participants in blue carbon trading, as well as their objective needs, this paper develops an evolutionary game model consisting of a demander, a supplier, the government, and a third-party institution to make a simulation analysis based on certain key parameters in order to determine how to maximize efficiency of blue carbon trading. The results show: (1) an extraordinarily high or low price will simply benefit one party to a transaction, but at considerable cost to the interests of the other party, which hence is unfavorable to blue carbon trading in the long run; (2) the government may increase, directly or indirectly, the willingness of the other three parties to participate in the trading through appropriate regulations, especially through adjustments to the emission quotas, which has the most significant impacts on overall blue carbon trading; (3) although the final choices of the demander, supplier, and third-party institution on whether to participate in a transaction are generally consistent, nonetheless, high derivative values of blue carbon products may drive the supplier to continue to engage in the related industry even when the demander has no purchase intent. In this case, the supplier does objectively provide a continuous supply of blue carbon, though it does not subjectively intend to do so.

Suggested Citation

  • He, Yixiong & Zhang, Fengxuan & Wang, Yanwei, 2023. "How to facilitate efficient blue carbon trading? A simulation study using the game theory to find the optimal strategy for each participant," Energy, Elsevier, vol. 276(C).
  • Handle: RePEc:eee:energy:v:276:y:2023:i:c:s0360544223009155
    DOI: 10.1016/j.energy.2023.127521
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223009155
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2023.127521?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. Qingxian An & Kefan Zhu & Beibei Xiong & Zhiyang Shen, 2023. "Carbon resource reallocation with emission quota in carbon emission trading system," Post-Print hal-03974850, HAL.
    2. Zhaofu Hong & Chengbin Chu & Linda Zhang & Yugang Yu, 2017. "Optimizing an emission trading scheme for local governments: A Stackelberg game model and hybrid algorithm," Post-Print hal-01745365, HAL.
    3. Peter U. Clark & Jeremy D. Shakun & Shaun A. Marcott & Alan C. Mix & Michael Eby & Scott Kulp & Anders Levermann & Glenn A. Milne & Patrik L. Pfister & Benjamin D. Santer & Daniel P. Schrag & Susan So, 2016. "Consequences of twenty-first-century policy for multi-millennial climate and sea-level change," Nature Climate Change, Nature, vol. 6(4), pages 360-369, April.
    4. Qi, Haozhi & Wu, Tiantian & Chen, Hao & Lu, Xiuling, 2023. "Time-frequency connectedness and cross-quantile dependence between carbon emission trading and commodity markets: Evidence from China," Resources Policy, Elsevier, vol. 82(C).
    5. Lukas, Elmar & Welling, Andreas, 2014. "Timing and eco(nomic) efficiency of climate-friendly investments in supply chains," European Journal of Operational Research, Elsevier, vol. 233(2), pages 448-457.
    6. Daniel Friedman, 1998. "On economic applications of evolutionary game theory," Journal of Evolutionary Economics, Springer, vol. 8(1), pages 15-43.
    7. Ritzberger, Klaus & Weibull, Jorgen W, 1995. "Evolutionary Selection in Normal-Form Games," Econometrica, Econometric Society, vol. 63(6), pages 1371-1399, November.
    8. Bolton, Patrick & Kacperczyk, Marcin, 2021. "Do investors care about carbon risk?," Journal of Financial Economics, Elsevier, vol. 142(2), pages 517-549.
    9. Zhang, Shengling & Wang, Yao & Hao, Yu & Liu, Zhiwei, 2021. "Shooting two hawks with one arrow: Could China's emission trading scheme promote green development efficiency and regional carbon equality?," Energy Economics, Elsevier, vol. 101(C).
    10. Yang, Lei & Zhang, Qin & Ji, Jingna, 2017. "Pricing and carbon emission reduction decisions in supply chains with vertical and horizontal cooperation," International Journal of Production Economics, Elsevier, vol. 191(C), pages 286-297.
    11. Weng, Qingqing & Xu, He, 2018. "A review of China’s carbon trading market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 613-619.
    12. Gao, Yuning & Li, Meng & Xue, Jinjun & Liu, Yu, 2020. "Evaluation of effectiveness of China's carbon emissions trading scheme in carbon mitigation," Energy Economics, Elsevier, vol. 90(C).
    13. Wei, Yigang & Liang, Xin & Xu, Liang & Kou, Gang & Chevallier, Julien, 2023. "Trading, storage, or penalty? Uncovering firms' decision-making behavior in the Shanghai emissions trading scheme: Insights from agent-based modeling," Energy Economics, Elsevier, vol. 117(C).
    14. Hong, Zhaofu & Chu, Chengbin & Zhang, Linda L. & Yu, Yugang, 2017. "Optimizing an emission trading scheme for local governments: A Stackelberg game model and hybrid algorithm," International Journal of Production Economics, Elsevier, vol. 193(C), pages 172-182.
    15. Hu, Yu & Chi, Yuanying & Zhou, Wenbing & Li, Jialin & Wang, Zhengzao & Yuan, Yongke, 2023. "The interactions between renewable portfolio standards and carbon emission trading in China: An evolutionary game theory perspective," Energy, Elsevier, vol. 271(C).
    16. Xu, Xiaofeng & Cui, Xiaodan & Chen, Xiangyu & Zhou, Yichen, 2022. "Impact of government subsidies on the innovation performance of the photovoltaic industry: Based on the moderating effect of carbon trading prices," Energy Policy, Elsevier, vol. 170(C).
    17. Yang, Shengyi, 2023. "Carbon emission trading policy and firm's environmental investment," Finance Research Letters, Elsevier, vol. 54(C).
    18. Zheng, Shan & Yu, Lianghong, 2022. "The government's subsidy strategy of carbon-sink fishery based on evolutionary game," Energy, Elsevier, vol. 254(PB).
    19. Wang, Kai-Hua & Liu, Lu & Zhong, Yifan & Lobonţ, Oana-Ramona, 2022. "Economic policy uncertainty and carbon emission trading market: A China's perspective," Energy Economics, Elsevier, vol. 115(C).
    20. Chen, Shuyang & Wang, Can, 2023. "Inequality impacts of ETS penalties: A case study on the recent Chinese nationwide ETS market," Energy Policy, Elsevier, vol. 173(C).
    21. Carl-Friedrich Schleussner & Joeri Rogelj & Michiel Schaeffer & Tabea Lissner & Rachel Licker & Erich M. Fischer & Reto Knutti & Anders Levermann & Katja Frieler & William Hare, 2016. "Science and policy characteristics of the Paris Agreement temperature goal," Nature Climate Change, Nature, vol. 6(9), pages 827-835, September.
    22. Yue Wu & Kaifu Zhang & Jinhong Xie, 2020. "Bad Greenwashing, Good Greenwashing: Corporate Social Responsibility and Information Transparency," Management Science, INFORMS, vol. 66(7), pages 3095-3112, July.
    23. Ji, Shou-feng & Zhao, Dan & Luo, Rong-juan, 2019. "Evolutionary game analysis on local governments and manufacturers' behavioral strategies: Impact of phasing out subsidies for new energy vehicles," Energy, Elsevier, vol. 189(C).
    Full references (including those not matched with items on IDEAS)

    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. Liu, Yang & Cui, Mengying & Gao, Xubin, 2023. "Building up scrap steel bases for perfecting scrap steel industry chain in China: An evolutionary game perspective," Energy, Elsevier, vol. 278(C).
    2. Liu, Jicheng & Sun, Jiakang & Yuan, Hanying & Su, Yihan & Feng, Shuxian & Lu, Chaoran, 2022. "Behavior analysis of photovoltaic-storage-use value chain game evolution in blockchain environment," Energy, Elsevier, vol. 260(C).
    3. Daozhi Zhao & Jiaqin Hao & Cejun Cao & Hongshuai Han, 2019. "Evolutionary Game Analysis of Three-Player for Low-Carbon Production Capacity Sharing," Sustainability, MDPI, vol. 11(11), pages 1-20, May.
    4. Hans B. Christensen & Luzi Hail & Christian Leuz, 2021. "Mandatory CSR and sustainability reporting: economic analysis and literature review," Review of Accounting Studies, Springer, vol. 26(3), pages 1176-1248, September.
    5. Lee, Jun-Yeon & Choi, Sungyong, 2021. "Supply chain investment and contracting for carbon emissions reduction: A social planner's perspective," International Journal of Production Economics, Elsevier, vol. 231(C).
    6. Hafezi, Maryam & Zolfagharinia, Hossein, 2018. "Green product development and environmental performance: Investigating the role of government regulations," International Journal of Production Economics, Elsevier, vol. 204(C), pages 395-410.
    7. Xia, Xiaoning & Li, Pengwei & Cheng, Yang, 2023. "Tripartite evolutionary game analysis of power battery carbon footprint disclosure under the EU battery regulation," Energy, Elsevier, vol. 284(C).
    8. Zihan Zhang & Junkang Song & Wanjiang Wang, 2023. "Study on the Behavior Strategy of the Subject of Low-Carbon Retrofit of Residential Buildings Based on Tripartite Evolutionary Game," Sustainability, MDPI, vol. 15(9), pages 1-25, May.
    9. Song, Xiang & Wang, Dingyu & Zhang, Xuantao & He, Yuan & Wang, Yong, 2022. "A comparison of the operation of China's carbon trading market and energy market and their spillover effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    10. Qianwen Wu & Qiangqiang Wang & Yongwu Dai, 2023. "Analysis of Strategy Selection in Third-Party Governance of Rural Environmental Pollution," Sustainability, MDPI, vol. 15(11), pages 1-19, May.
    11. Teng, Minmin & Lv, Kunfeng & Han, Chuanfeng & Liu, Pihui, 2023. "Trading behavior strategy of power plants and the grid under renewable portfolio standards in China: A tripartite evolutionary game analysis," Energy, Elsevier, vol. 284(C).
    12. Ma, Miaomiao & Meng, Weidong & Li, Yuyu & Huang, Bo, 2023. "Impact of dual credit policy on new energy vehicles technology innovation with information asymmetry," Applied Energy, Elsevier, vol. 332(C).
    13. Zhang, Xiaoyan & Zhu, Shanying & He, Jianping & Yang, Bo & Guan, Xinping, 2019. "Credit rating based real-time energy trading in microgrids," Applied Energy, Elsevier, vol. 236(C), pages 985-996.
    14. Zhang, Jiayu & Yang, Xiaodong & Wang, Hao, 2021. "Age-friendly regeneration of urban settlements in China: Game and incentives of stakeholders in decision-making," Land Use Policy, Elsevier, vol. 111(C).
    15. Wang, Yadong & Mao, Jinqi & Chen, Fan & Wang, Delu, 2022. "Uncovering the dynamics and uncertainties of substituting coal power with renewable energy resources," Renewable Energy, Elsevier, vol. 193(C), pages 669-686.
    16. Guang Zhu & Gaozhi Pan & Weiwei Zhang, 2018. "Evolutionary Game Theoretic Analysis of Low Carbon Investment in Supply Chains under Governmental Subsidies," IJERPH, MDPI, vol. 15(11), pages 1-27, November.
    17. Xiaoyan Li & Hengzhou Xu, 2020. "Effect of local government decision‐making competition on carbon emissions: Evidence from China's three urban agglomerations," Business Strategy and the Environment, Wiley Blackwell, vol. 29(6), pages 2418-2431, September.
    18. Lurdes Jesus Ferreira & Luís Pereira Dias & Jieling Liu, 2022. "Adopting Carbon Pricing Tools at the Local Level: A City Case Study in Portugal," Sustainability, MDPI, vol. 14(3), pages 1-20, February.
    19. Panagiotis Koromilas & Angeliki Mathioudaki & Sotirios Dimos & Dimitris Fotakis, 2023. "Modeling Intertemporal Trading of Emission Permits Under Market Power," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(1), pages 241-278, January.
    20. Long, Wenbin & Qu, Xin & Yin, Saifeng, 2023. "How does carbon emissions trading policy affect accrued earnings management in corporations? Evidence from China," Finance Research Letters, Elsevier, vol. 55(PA).

    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:energy:v:276:y:2023:i:c:s0360544223009155. 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.journals.elsevier.com/energy .

    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.