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Research on Digital Technology to Promote Low-Carbon Transformation of Manufacturing Industries Under the Perspective of Green Credit: An Evolutionary Game Theory Approach

Author

Listed:
  • Zeguo Qiu

    (School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China
    Heilongjiang Provincial Research Center for Cultural Big Data Theory and Application, Harbin 150028, China)

  • Yunhao Chen

    (School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China)

  • Hao Han

    (School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China)

  • Tianyu Wang

    (School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China)

Abstract

With the increasing global concern for environmental protection and sustainable development, the low-carbon transformation of the manufacturing industries has become a top priority. The rapid development of green digital technology (GDT) provides new opportunities and a strong impetus for the low-carbon transformation of the manufacturing industries. Meanwhile, green credit, as an important financial tool to promote the development of the green economy, plays a key role in guiding resource allocation. In order to respond to the urgent global demand for environmental protection and sustainable development and to accelerate the pace of the low-carbon transformation of manufacturing industries, based on evolutionary game theory, this paper constructs a three-party evolutionary game model of commercial banks (CBs), digital businesses (DBs) and manufacturing industries (MIs); further subdivides the MIs into two categories of non-polluting MIs and polluting Mis; and performs a numerical simulation using Python to analyze the influence of the main parameters on the evolutionary stabilization strategy. The results of the study are as follows: (1) Changes in the interest rate of the green credit have a greater impact on the strategic evolution process of polluting MIs than non-polluting MIs. The green credit model contributes to the introduction of GDT for the low-carbon transformation by non-polluting MIs, although for polluting MIs, the model hinders, to some extent, their introduction of GDT for the low-carbon transformation. (2) Polluting MIs are more sensitive to the investment cost of introducing GDT than non-polluting MIs. When the support benefits of GDT are too low, polluting MIs are more inclined to choose independent innovation to realize the low-carbon transition. (3) Government subsidies to DBs in terms of GDT innovation are crucial to the DBs’ strategy choices. High subsidies can significantly accelerate the cooperation process between DBs and Mis. The findings reveal the challenges and opportunities faced by both non-polluting and polluting manufacturing industries in the process of the low-carbon transformation. In addition, the study provides theoretical references for the behavioral decisions of commercial banks, digital businesses, and manufacturing industries, and proposes corresponding management suggestions to promote the sustainable development of the manufacturing industries.

Suggested Citation

  • Zeguo Qiu & Yunhao Chen & Hao Han & Tianyu Wang, 2024. "Research on Digital Technology to Promote Low-Carbon Transformation of Manufacturing Industries Under the Perspective of Green Credit: An Evolutionary Game Theory Approach," Sustainability, MDPI, vol. 16(24), pages 1-27, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:24:p:11203-:d:1548679
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    References listed on IDEAS

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