Exploring Digital-Driven Pathways for Green and Low-Carbon Development: A Survey of Chinese Cities

Green and low-carbon development (GLD) is central to facilitating the high-quality transitional development of economic and social sectors, as well as to the achievement of China’s “dual carbon” goals. The digital economy (DE), a burgeoning economic paradigm, serves as a potent driver for GLD by leveraging its intrinsic strengths in innovation-led growth and cross-sectoral industrial integration. Drawing on the TOE (Technology-Organization-Environment) framework, this study employs dynamic Qualitative Comparative Analysis (QCA) and regression analysis to examine panel data (2014–2023) of 44 core coastal cities in the Yangtze River Economic Belt, aiming to identify the driving paths of GLD. The research results indicate that a single dimension in the DE cannot constitute the necessary condition for regional GLD. Specifically, there are 6 configurational paths for high-level GLD (categorized into “organization-led” and “technology-organization-environment multi-driven” models) and 3 paths for low-level GLD (summarized as “three-dimensional constraint” and “technology-organization deficiency” models). In terms of the driving effect, the technology-organization-environment multi-driven configurational path exerts the strongest promotional effect on regional GLD. This study yields a valuable theoretical foundation for understanding the synergistic role of multidimensional DE elements in driving GLD, while also delivering actionable insights for local governments to identify contextually tailored GLD trajectories.

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Publication Details

Journal
Sustainability
Published
2025-10-24
DOI
https://doi.org/10.3390/su17219452
Citations
1
Primary Topic
Qualitative Comparative Analysis Research
Type
article
Field-Weighted Citation Impact
4.20
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article

Exploring Digital-Driven Pathways for Green and Low-Carbon Development: A Survey of Chinese Cities

X.L. Pei Y.H. Liu H.Y. Li, Yingting Qin, Huafei Yan
1 citations
Sustainability
Qualitative Comparative Analysis Research
4.20
article

Exploring Digital-Driven Pathways for Green and Low-Carbon Development: A Survey of Chinese Cities

X.L. Pei Y.H. Liu H.Y. Li, Yingting Qin, Huafei Yan
article en
1 citations

Abstract

Green and low-carbon development (GLD) is central to facilitating the high-quality transitional development of economic and social sectors, as well as to the achievement of China’s “dual carbon” goals. The digital economy (DE), a burgeoning economic paradigm, serves as a potent driver for GLD by leveraging its intrinsic strengths in innovation-led growth and cross-sectoral industrial integration. Drawing on the TOE (Technology-Organization-Environment) framework, this study employs dynamic Qualitative Comparative Analysis (QCA) and regression analysis to examine panel data (2014–2023) of 44 core coastal cities in the Yangtze River Economic Belt, aiming to identify the driving paths of GLD. The research results indicate that a single dimension in the DE cannot constitute the necessary condition for regional GLD. Specifically, there are 6 configurational paths for high-level GLD (categorized into “organization-led” and “technology-organization-environment multi-driven” models) and 3 paths for low-level GLD (summarized as “three-dimensional constraint” and “technology-organization deficiency” models). In terms of the driving effect, the technology-organization-environment multi-driven configurational path exerts the strongest promotional effect on regional GLD. This study yields a valuable theoretical foundation for understanding the synergistic role of multidimensional DE elements in driving GLD, while also delivering actionable insights for local governments to identify contextually tailored GLD trajectories.

SustainabilityVol. 17(21)
Wuhan Institute of Technology (CN)
Openalex Percentile: Top 5%
Qualitative Comparative Analysis Research
4.20
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Exploring Digital-Driven Pathways for Green and Low-Carbon Development: A Survey of Chinese Cities — X.L. Pei Y.H. Liu H.Y. Li, Yingting Qin, et al. · Sustainability (2025) | TGRS Research Map | TGRS