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Mechanism Analysis of Applying Blockchain Technology to Forestry Carbon Sink Projects Based on the Differential Game Model

Author

Listed:
  • Rui Sun

    (School of Economics and Management, China University of Geosciences, Beijing 100083, China)

  • Dayi He

    (School of Economics and Management, China University of Geosciences, Beijing 100083, China)

  • Jingjing Yan

    (School of Economics and Management, China University of Geosciences, Beijing 100083, China)

  • Li Tao

    (School of Economics and Management, China University of Geosciences, Beijing 100083, China)

Abstract

As an important way to reduce emission, forestry carbon sink (FCS) has not been implemented effectively. Therefore, this paper aims to analyze the effectiveness and mechanism of applying blockchain technology in FCS projects by utilizing the differential game model. A Stackelberg differential game model between forest farmers and emission-controlled enterprises (ECEs) is developed to analyze the optimal emission reduction efforts and the optimal trajectory of forest farmers and ECEs before and after introducing blockchain technology. It is found that: (1) At the initial stage of the utilization of blockchain technology, if blockchain technology takes a leading role in stabilizing carbon prices, the ECEs prefer to purchase FCS instead of reducing emissions by their own technology. On the contrary, if blockchain technology takes a leading role in stimulating the vitality of the carbon trading market, ECEs tend to use emission abatement technology to meet the carbon quote requirements. (2) In the later stage, the incentive and stabilizing effects of blockchain technology on carbon prices tend to be balanced, and the emission reduction efforts of ECEs are lower than the efforts before applying blockchain technology. (3) The application of blockchain technology increases forest farmers’ willingness to reduce emissions because of its effection of cost reduction and efficiency improvement. Meanwhile, blockchain technology reduces abatement costs by influencing carbon prices. Therefore, blockchain technology improves forest farmers’ emission reduction efforts on the whole.

Suggested Citation

  • Rui Sun & Dayi He & Jingjing Yan & Li Tao, 2021. "Mechanism Analysis of Applying Blockchain Technology to Forestry Carbon Sink Projects Based on the Differential Game Model," Sustainability, MDPI, vol. 13(21), pages 1-18, October.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11697-:d:662734
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    References listed on IDEAS

    as
    1. Lin, Boqiang & Ge, Jiamin, 2021. "Does institutional freedom matter for global forest carbon sinks in the face of economic development disparity?," China Economic Review, Elsevier, vol. 65(C).
    2. Alisa E White & David A Lutz & Richard B Howarth & José R Soto, 2018. "Small-scale forestry and carbon offset markets: An empirical study of Vermont Current Use forest landowner willingness to accept carbon credit programs," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-24, August.
    3. Elkhan Richard Sadik-Zada, 2021. "An Ode to ODA against all Odds? A Novel Game-Theoretical and Empirical Reappraisal of the Terrorism-Aid Nexus," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 49(2), pages 221-240, June.
    4. Michael Wang & Bill Wang & Ahmad Abareshi, 2020. "Blockchain Technology and Its Role in Enhancing Supply Chain Integration Capability and Reducing Carbon Emission: A Conceptual Framework," Sustainability, MDPI, vol. 12(24), pages 1-17, December.
    5. Khaqqi, Khamila Nurul & Sikorski, Janusz J. & Hadinoto, Kunn & Kraft, Markus, 2018. "Incorporating seller/buyer reputation-based system in blockchain-enabled emission trading application," Applied Energy, Elsevier, vol. 209(C), pages 8-19.
    6. Elkhan Richard Sadik-Zada, 2020. "Distributional Bargaining and the Speed of Structural Change in the Petroleum Exporting Labor Surplus Economies," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 32(1), pages 51-98, January.
    7. Per Gundersen & Emil E. Thybring & Thomas Nord-Larsen & Lars Vesterdal & Knute J. Nadelhoffer & Vivian K. Johannsen, 2021. "Old-growth forest carbon sinks overestimated," Nature, Nature, vol. 591(7851), pages 21-23, March.
    8. Hua, Weiqi & Jiang, Jing & Sun, Hongjian & Wu, Jianzhong, 2020. "A blockchain based peer-to-peer trading framework integrating energy and carbon markets," Applied Energy, Elsevier, vol. 279(C).
    9. Khanal, Puskar N. & Grebner, Donald L. & Straka, Thomas J. & Adams, Damian C., 2019. "Obstacles to participation in carbon sequestration for nonindustrial private forest landowners in the southern United States: A diffusion of innovations perspective," Forest Policy and Economics, Elsevier, vol. 100(C), pages 95-101.
    10. Mark R. Gleim & Jennifer L. Stevens, 2021. "Blockchain: a game changer for marketers?," Marketing Letters, Springer, vol. 32(1), pages 123-128, March.
    11. Shangrong Jiang & Yuze Li & Quanying Lu & Yongmiao Hong & Dabo Guan & Yu Xiong & Shouyang Wang, 2021. "Policy assessments for the carbon emission flows and sustainability of Bitcoin blockchain operation in China," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    12. Chuang, Tsai-Jen & Yen, Tian-Ming, 2017. "Public views on the value of forests in relation to forestation projects—A case study in central Taiwan," Forest Policy and Economics, Elsevier, vol. 78(C), pages 173-179.
    13. Sam Hartmann & Sebastian Thomas, 2020. "Applying Blockchain to the Australian Carbon Market," Economic Papers, The Economic Society of Australia, vol. 39(2), pages 133-151, June.
    14. Lingling Qiu & Weizhong Zeng & Shashi Kant & Sen Wang, 2021. "The Role of Social Capital in Rural Households’ Perceptions toward the Benefits of Forest Carbon Sequestration Projects: Evidence from a Rural Household Survey in Sichuan and Yunnan Provinces, China," Land, MDPI, vol. 10(2), pages 1-16, January.
    15. Caulkins, Jonathan P. & Feichtinger, Gustav & Grass, Dieter & Hartl, Richard F. & Kort, Peter M. & Seidl, Andrea, 2017. "Interaction of pricing, advertising and experience quality: A dynamic analysis," European Journal of Operational Research, Elsevier, vol. 256(3), pages 877-885.
    16. Ye Song & Hongjun Peng, 2019. "Strategies of Forestry Carbon Sink under Forest Insurance and Subsidies," Sustainability, MDPI, vol. 11(17), pages 1-13, August.
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    5. Hongyi Liu & Tianyu He, 2023. "Sustainable Management of Land Resources: The Case of China’s Forestry Carbon Sink Mechanism," Land, MDPI, vol. 12(6), pages 1-18, June.

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