Digitalization, Environmental Regulation, and Carbon Productivity: Evidence from China
This study incorporates digital factors into the corporate production function and extends the firm-level pollution emission decision-making model. From both technological and structural perspectives, it examines the mechanisms through which digitalization influences carbon productivity. An orthogonal projection-based dynamic evaluation framework is employed to quantify the level of digitalization across Chinese provinces for the period 2011–2022. On this basis, fixed effects, mediation, and partially linear functional-coefficient models are applied to analyze how digitalization affects carbon productivity and its boundary conditions. The results indicate that digitalization significantly enhances carbon productivity, primarily through technological diffusion, industrial restructuring, and energy decarbonization. The results are confirmed by multiple robustness tests. Moreover, environmental regulation plays a nonlinear moderating role, resulting in an inverted U-shaped relationship between digitalization and carbon productivity. When environmental regulation is weak, digitalization crowds out carbon reduction investment, thereby suppressing carbon productivity. As environmental regulation intensifies, the positive impact of digitalization on carbon productivity strengthens. However, once regulation exceeds a certain threshold, digitalization begins to hinder carbon productivity. This study verifies the applicability of the “Porter Hypothesis” in China from the viewpoint of digitalization and offers policy implications for better alignment between digital development and environmental regulation.
Authors
- Yanfang Lyu (ORCID: https://orcid.org/0000-0003-0182-1364)
- Dong Wang (ORCID: https://orcid.org/0000-0001-9454-3126)
- Leifeng Zhang
Institutions
- Guangdong University of Technology (CN)
- Henan University of Urban Construction (CN)
- Minnan Normal University (CN)
Publication Details
- Journal
- Journal of Advanced Computational Intelligence and Intelligent Informatics
- Published
- 2026-09-19
- DOI
- https://doi.org/10.20965/jaciii.2026.p1377
- Primary Topic
- Energy, Environment, Economic Growth
- Type
- article
- Field-Weighted Citation Impact
- 0.00