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Golden-Edged Dark Clouds: Climate Policy Uncertainty and Corporate Intelligent Transformation

Author

Listed:
  • Tengfei Jiang

    (School of Finance and Economics, Jiangsu University, Zhenjiang 212000, China)

  • Jiayi Liu

    (School of Finance and Economics, Jiangsu University, Zhenjiang 212000, China)

  • Jie Dai

    (School of Finance and Economics, Jiangsu University, Zhenjiang 212000, China)

  • Hongli Jiang

    (School of Finance and Economics, Jiangsu University, Zhenjiang 212000, China)

Abstract

Climate policy uncertainty (CPU) poses formidable challenges to global sustainable development and corporate strategic planning, while intelligent transformation is emerging as a pivotal enabler of organizational sustainability. Using panel data from Chinese A-share listed companies between 2011 and 2022, this study investigates the impact of climate policy uncertainty on intelligent transformation. The results indicate that CPU significantly promotes corporate intelligent transformation, a conclusion that remains robust under various sensitivity tests. Government innovation subsidies, enterprise absorption capacity, and enterprise human capital positively moderate this facilitating effect. A heterogeneity analysis reveals that the effect of CPU on intelligent transformation is more pronounced among firms in sci–tech finance pilot zones, regions with high digital financial inclusion, and those led by CEOs with banking experience. This paper contributes to the literature on climate policy uncertainty by examining its role in corporate intelligent transformation, offering actionable strategies for firms to mitigate climate risks while providing policy insights for developing economies to leverage smart technologies in addressing CPU.

Suggested Citation

  • Tengfei Jiang & Jiayi Liu & Jie Dai & Hongli Jiang, 2025. "Golden-Edged Dark Clouds: Climate Policy Uncertainty and Corporate Intelligent Transformation," Sustainability, MDPI, vol. 17(11), pages 1-21, June.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:11:p:5162-:d:1671739
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