IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i4p3643-d1073090.html
   My bibliography  Save this article

ESG Investment Scale Allocation of China’s Power Grid Company Using System Dynamics Simulation Modeling

Author

Listed:
  • Birong Huang

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

  • Zilong Wang

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

  • Yuan Gu

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

Abstract

In recent years, with the global recognition of the concept of sustainable development, the international market attaches great importance to the Environment, Society, and Governance (ESG) investment performance of enterprises. The “carbon peaking and carbon neutrality” goal puts forward requirements for Chinese enterprises to carry out ESG investment. As a large state-owned enterprise in China, power grid companies need to take the lead in ESG investment. Based on the System Dynamics (SD) theory, this paper establishes the simulation model of ESG-responsible investment of power grid companies, including the environmental investment sub-module, social investment sub-module, and governance investment sub-module. Taking a provincial Power Grid Company as an example, the numerical simulation of ESG investment of power grid companies is carried out. The actual input-output efficiency of ESG investment of power grid companies is reflected through the mapping relationship between key indicators and investment amount, and the ESG investment scale and investment weight of the Power Company in the coming years are predicted. Compared with the traditional static analysis method, this model can provide a theoretical basis for power grid companies to carry out ESG investment decisions.

Suggested Citation

  • Birong Huang & Zilong Wang & Yuan Gu, 2023. "ESG Investment Scale Allocation of China’s Power Grid Company Using System Dynamics Simulation Modeling," IJERPH, MDPI, vol. 20(4), pages 1-16, February.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:4:p:3643-:d:1073090
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/4/3643/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/20/4/3643/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fatemi, Ali & Glaum, Martin & Kaiser, Stefanie, 2018. "ESG performance and firm value: The moderating role of disclosure," Global Finance Journal, Elsevier, vol. 38(C), pages 45-64.
    2. Wen, Hui & Ho, Ken C. & Gao, Jijun & Yu, Li, 2022. "The fundamental effects of ESG disclosure quality in boosting the growth of ESG investing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    3. He, Y.X. & Jiao, J. & Chen, R.J. & Shu, H., 2018. "The optimization of Chinese power grid investment based on transmission and distribution tariff policy: A system dynamics approach," Energy Policy, Elsevier, vol. 113(C), pages 112-122.
    4. Ioannis Passas & Konstantina Ragazou & Eleni Zafeiriou & Alexandros Garefalakis & Constantin Zopounidis, 2022. "ESG Controversies: A Quantitative and Qualitative Analysis for the Sociopolitical Determinants in EU Firms," Sustainability, MDPI, vol. 14(19), pages 1-17, October.
    5. SiJian Niu & Byung Il Park & Jin Sup Jung, 2022. "The Effects of Digital Leadership and ESG Management on Organizational Innovation and Sustainability," Sustainability, MDPI, vol. 14(23), pages 1-20, November.
    6. Dariush Khezrimotlagh & Yao Chen, 2018. "The Optimization Approach," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 107-134, Springer.
    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. Fengxue Yin & Yanling Xiao & Rui Cao & Jianhua Zhang, 2023. "Impacts of ESG Disclosure on Corporate Carbon Performance: Empirical Evidence from Listed Companies in Heavy Pollution Industries," Sustainability, MDPI, vol. 15(21), pages 1-19, October.
    2. Wu, Jiansong & Zhang, Linlin & Bai, Yiping & Reniers, Genserik, 2022. "A safety investment optimization model for power grid enterprises based on System Dynamics and Bayesian network theory," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    3. Darya Pyatkina & Tamara Shcherbina & Vadim Samusenkov & Irina Razinkina & Mariusz Sroka, 2021. "Modeling and Management of Power Supply Enterprises’ Cash Flows," Energies, MDPI, vol. 14(4), pages 1-17, February.
    4. Liu, Dunnan & Xiao, Bowen, 2018. "Exploring the development of electric vehicles under policy incentives: A scenario-based system dynamics model," Energy Policy, Elsevier, vol. 120(C), pages 8-23.
    5. Ye, Rui-Ke & Gao, Zhuang-Fei & Fang, Kai & Liu, Kang-Li & Chen, Jia-Wei, 2021. "Moving from subsidy stimulation to endogenous development: A system dynamics analysis of China's NEVs in the post-subsidy era," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    6. Wang, Yongli & Zhou, Minhan & Zhang, Fuli & Zhang, Yuli & Ma, Yuze & Dong, Huanran & Zhang, Danyang & Liu, Lin, 2021. "Chinese grid investment based on transmission and distribution tariff policy: An optimal coordination between capacity and demand," Energy, Elsevier, vol. 219(C).
    7. Hu, Yu & Chi, Yuanying & Zhao, Hao & Zhou, Wenbing, 2022. "The development of renewable energy industry under renewable portfolio standards: From the perspective of provincial resource differences," Energy Policy, Elsevier, vol. 170(C).
    8. Izzet Alp Gul & Gülgün Kayakutlu & M. Özgür Kayalica, 2020. "Risk Analysis in Renewable Energy System (RES) Investment for a Developing Country: A Case Study in Pakistan," Arthaniti: Journal of Economic Theory and Practice, , vol. 19(2), pages 204-223, December.
    9. Yilmaz, S. & Rinaldi, A. & Patel, M.K., 2020. "DSM interactions: What is the impact of appliance energy efficiency measures on the demand response (peak load management)?," Energy Policy, Elsevier, vol. 139(C).
    10. Dmitry Borisoglebsky & Liz Varga, 2019. "A Resilience Toolbox and Research Design for Black Sky Hazards to Power Grids," Complexity, Hindawi, vol. 2019, pages 1-15, June.
    11. Sen Guo & Wenyue Zhang & Xiao Gao, 2020. "Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method," Sustainability, MDPI, vol. 12(5), pages 1-21, March.
    12. Xu, Xiaomin & Niu, Dongxiao & Xiao, Bowen & Guo, Xiaodan & Zhang, Lihui & Wang, Keke, 2020. "Policy analysis for grid parity of wind power generation in China," Energy Policy, Elsevier, vol. 138(C).
    13. Wu, Zhongqun & Zheng, Ruijin, 2022. "Research on the impact of financial transmission rights on transmission expansion: A system dynamics model," Energy, Elsevier, vol. 239(PA).
    14. Lei Gao & Zhen-Yu Zhao & Cui Li, 2022. "An Investment Decision-Making Approach for Power Grid Projects: A Multi-Objective Optimization Model," Energies, MDPI, vol. 15(3), pages 1-20, February.
    15. Schreiner, Lena & Madlener, Reinhard, 2021. "A pathway to green growth? Macroeconomic impacts of power grid infrastructure investments in Germany," Energy Policy, Elsevier, vol. 156(C).
    16. Esmaieli, M. & Ahmadian, M., 2018. "The effect of research and development incentive on wind power investment, a system dynamics approach," Renewable Energy, Elsevier, vol. 126(C), pages 765-773.
    17. Wang, Yongli & Zhang, Fuli & Zhang, Yuanyuan & Wang, Xiaohai & Fan, Lisha & Song, Fuhao & Ma, Yuze & Wang, Shuo, 2019. "Chinese power-grid financial capacity based on transmission and distribution tariff policy: A system dynamics approach," Utilities Policy, Elsevier, vol. 60(C), pages 1-1.
    18. Jingqi Sun & Nuermaimaiti Ruze & Jianjun Zhang & Haoran Zhao & Boyang Shen, 2019. "Evaluating the Investment Efficiency of China’s Provincial Power Grid Enterprises under New Electricity Market Reform: Empirical Evidence Based on Three-Stage DEA Model," Energies, MDPI, vol. 12(18), pages 1-17, September.
    19. Wang, Yongli & Wang, Yudong & Huang, Yujing & Yang, Jiale & Ma, Yuze & Yu, Haiyang & Zeng, Ming & Zhang, Fuwei & Zhang, Yanfu, 2019. "Operation optimization of regional integrated energy system based on the modeling of electricity-thermal-natural gas network," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    20. Yang, Lin & Pang, Shujiang & Wang, Xiaoyan & Du, Yi & Huang, Jieyu & Melching, Charles S., 2021. "Optimal allocation of best management practices based on receiving water capacity constraints," Agricultural Water Management, Elsevier, vol. 258(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:jijerp:v:20:y:2023:i:4:p:3643-:d:1073090. 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.