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The Impact of the Low-Carbon Energy Concept and Green Transition on Corporate Behaviour—A Perspective Based on a Contagion Model

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Listed:
  • Shuran Wen

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

  • Wei Cui

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

  • Guiying Wei

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

Abstract

With the globalisation of the economy and the increasing interconnectedness of individuals in the financial markets, companies implementing high energy consumption strategies have become more widespread due to the “herding effect” as they become more closely linked for development. In the context of carbon neutrality, the issue of how to reduce the spread of high energy consumption strategies and the issue surrounding the governance of corporate emissions have become a focus of research. This paper uses the improved SEIJRS infectious disease model to investigate the phenomenon of corporate high energy strategy infection, combined with optimal control theory, to provide a reference for governments and regulators to develop reasonable optimal prevention and control strategies.

Suggested Citation

  • Shuran Wen & Wei Cui & Guiying Wei, 2022. "The Impact of the Low-Carbon Energy Concept and Green Transition on Corporate Behaviour—A Perspective Based on a Contagion Model," Sustainability, MDPI, vol. 14(24), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16600-:d:1000216
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    1. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    2. Ates, Seyithan Ahmet & Durakbasa, Numan M., 2012. "Evaluation of corporate energy management practices of energy intensive industries in Turkey," Energy, Elsevier, vol. 45(1), pages 81-91.
    3. Bhaskar Bagchi & Susmita Chatterjee & Raktim Ghosh & Dhrubaranjan Dandapat, 2020. "Impact of COVID-19 on Global Economy," SpringerBriefs in Economics, in: Coronavirus Outbreak and the Great Lockdown, chapter 3, pages 15-26, Springer.
    4. Zhang, Yixiang & Zhou, Weiyi & Liu, Meiling, 2022. "Driving factors of enterprise energy-saving and emission reduction behaviors," Energy, Elsevier, vol. 256(C).
    5. Kee-Hong Bae & G. Andrew Karolyi & René M. Stulz, 2003. "A New Approach to Measuring Financial Contagion," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 717-763, July.
    6. Yuanyuan Ma & Lingxuan Li, 2018. "Crisis Spreading Model of the Shareholding Networks of Listed Companies and Their Main Holders and Their Controllability," Complexity, Hindawi, vol. 2018, pages 1-17, December.
    7. Zhao, Laijun & Cui, Hongxin & Qiu, Xiaoyan & Wang, Xiaoli & Wang, Jiajia, 2013. "SIR rumor spreading model in the new media age," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 995-1003.
    8. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    9. Weisong Mi & Kaixu Zhao & Pei Zhang, 2022. "Spatio-Temporal Evolution and Driving Mechanism of Green Innovation in China," Sustainability, MDPI, vol. 14(9), pages 1-27, April.
    10. Qian, Qian & Yang, Yang & Gu, Jing & Feng, Hairong, 2019. "Information authenticity, spreading willingness and credit risk contagion – A dual-layer network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    11. Bhaskar Bagchi & Susmita Chatterjee & Raktim Ghosh & Dhrubaranjan Dandapat, 2020. "Coronavirus Outbreak and the Great Lockdown," SpringerBriefs in Economics, Springer, number 978-981-15-7782-6, October.
    12. King, Mervyn A & Wadhwani, Sushil, 1990. "Transmission of Volatility between Stock Markets," The Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 5-33.
    13. Dan Wang & Taiwen Feng & Alan Lawton, 2017. "Linking Ethical Leadership with Firm Performance: A Multi-dimensional Perspective," Journal of Business Ethics, Springer, vol. 145(1), pages 95-109, September.
    14. Linda Allen & Turan G. Bali & Yi Tang, 2012. "Does Systemic Risk in the Financial Sector Predict Future Economic Downturns?," The Review of Financial Studies, Society for Financial Studies, vol. 25(10), pages 3000-3036.
    15. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    16. Manli Cheng & Zhen Shao & Changhui Yang & Xiaoan Tang, 2019. "Analysis of Coordinated Development of Energy and Environment in China’s Manufacturing Industry under Environmental Regulation: A Comparative Study of Sub-Industries," Sustainability, MDPI, vol. 11(22), pages 1-20, November.
    17. Li, Li & Wang, Jianjun & Tan, Zhongfu & Ge, Xinquan & Zhang, Jian & Yun, Xiaozhe, 2014. "Policies for eliminating low-efficiency production capacities and improving energy efficiency of energy-intensive industries in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 312-326.
    18. Zhou, P. & Wen, Wen, 2020. "Carbon-constrained firm decisions: From business strategies to operations modeling," European Journal of Operational Research, Elsevier, vol. 281(1), pages 1-15.
    19. Chen, Tingqiang & Wang, Jiepeng & Liu, Haifei & He, Yuanping, 2019. "Contagion model on counterparty credit risk in the CRT market by considering the heterogeneity of counterparties and preferential-random mixing attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 458-480.
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