Can digitalization promote cities' low-carbon development: Insights from local and neighboring regions
Year: 2025
Type: article
Abstract: Despite the widespread recognition of the importance of carbon reduction and the increasing prevalence of digital technologies, the exact nature of the relationship between digitalization and carbon emissions at the local and regional levels remains poorly understood. This lack of understanding hinders the development of targeted policies for achieving low-carbon urban development. This study aims to address the questions of whether digitalization can effectively contribute to carbon reduction and how digitalization impacts carbon emissions in different regions. Using panel data from 247 prefecture-level Chinese cities, we examine the synergistic effect of digitalization on carbon emissions in local and surrounding regions, as well as the underlying mechanisms involved. This benchmark research reveals that digitalization promotes low-carbon development through geographical spillover effects, in addition to facilitating low-carbon growth in local regions. The mechanistic analysis results indicate that digitalization promotes low-carbon growth via improvements in the energy structure and the stimulation of green technologies. According to the horizontal and vertical aspects of each region, heterogeneity analysis indicates that digitalization notably influences the reduction in urban carbon emissions in the central, western, and northern regions. This article offers policy proposals for accomplishing dual carbon goals and developing a new growth pattern, along with empirical data demonstrating that digitalization facilitates low-carbon urban development. • Digitalization facilitates low-carbon development in local regions. • Digitalization promotes low-carbon development in neighboring regions. • Improving the energy structure and green technology are the underlying mechanisms. • The impacts of digitalization on emissions are heterogeneous.
Source: Energy Strategy Reviews
Authors: Weijian Du, Yuhuan Fan, Nini Yuan, Mengjie Li
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $4,180
OpenAlex ID: W4408253543
