ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Environmental Policy and Governance
Volume 13 - 2025 | doi: 10.3389/fenvs.2025.1570182
This article is part of the Research TopicDigital Transformation in Construction: Integrating Metaverse, Digital Twin, and BIMView all 7 articles
Digital Transformation of Construction Enterprises and Carbon Emission Reduction: Evidence from Listed Companies
Provisionally accepted
- Hunan University of Finance and Economics, Changsha, China
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As a key field of energy consumption and carbon emission, the construction industry's carbon emission reduction measures have important strategic significance for achieving the goal of "double carbon". Based on the data of listed construction enterprises in China from 2000 to 2021, this paper empirically explores the effect and path of digital transformation on carbon emission reduction. The results show that digital transformation can significantly reduce the carbon emission intensity of enterprises, and it is mainly achieved through three paths: promoting green technology innovation, improving total factor productivity and optimizing production process and management structure. Heterogeneity analysis reveals that the effect of digital technology on emission reduction of enterprises with fierce competition in the industry is more significant, but the difference between regions is not significant. Further research shows that emerging technologies such as artificial intelligence and blockchain have more emission reduction potential than traditional information tools. The conclusion of this paper provides policy implications for the carbon-neutral path in the construction field.
Keywords: digital transformation of enterprises, Carbon emission reduction, Carbon emission of construction enterprises, Listed company, Dual Carbon Targets
Received: 03 Feb 2025; Accepted: 29 May 2025.
Copyright: © 2025 Zhao, Cao, Sui and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Sanglin Zhao, Hunan University of Finance and Economics, Changsha, China
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