Abstract
The concept of the “space of flows” emphasizes cross-space resource sharing arising from element flows in the digital age and has become an important topic in digital economy (DE) research. The DE is a key driver of global economic growth, whereas carbon emissions (CE) remain a major barrier to achieving global sustainable development goals. Existing research primarily examines the DE-CE relationship from a static perspective based on regional attributes. However, there is a lack of in-depth analysis on the digital economy spatial correlation network (DESCN) and its impact on CE from the perspective of the space of flows. This study aims to address this academic gap within the Chinese context. Our study applies the modified gravity model and social network analysis (SNA) method to characterize the DESCN, and further uses fuzzy set qualitative comparative analysis (fsQCA) to explore the network’s influence on CE. The key findings are as follows: (1) The DESCN exhibits multi-threaded and densifying characteristics, with increasingly frequent inter-regional cooperation, closer internal connections, and a continuously expanding overall scope. (2) While the DESCN exerts a significant overall impact on CE, its specific effects vary significantly. Simply elevating a region’s status within the network is not enough to achieve regional carbon reduction and may even result in increased emissions. (3) To fully unlock the carbon reduction potential of the DE, regions must consider other factors, including population size, energy consumption, industrial structure, and openness.
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Data Availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
Asongu SA, Le Roux S, Biekpe N (2018) Enhancing ICT for environmental sustainability in sub-Saharan Africa. Technol Forecast Soc Change 127:209–216. https://doi.org/10.1016/j.techfore.2017.09.022
Bai L, Guo T, Xu W, Liu Y, Kuang M, Jiang L (2023a) Effects of digital economy on carbon emission intensity in Chinese cities: A life-cycle theory and the application of non-linear spatial panel smooth transition threshold model. Energy Policy 183:113792. https://doi.org/10.1016/j.enpol.2023.113792
Bai T, Qi Y, Li Z, Xu D (2023b) Digital economy, industrial transformation and upgrading, and spatial transfer of carbon emissions: The paths for low-carbon transformation of Chinese cities. J Environ Manag 344:118528. https://doi.org/10.1016/j.jenvman.2023.118528
Balland PA, De Vaan M, Boschma R (2013) The dynamics of interfirm networks along the industry life cycle: The case of the global video game industry, 1987–2007. J Econ Geogr 13(5):741–765. https://doi.org/10.1093/jeg/lbs023
Cai B, Wang X, Huang G, Wang J, Cao D, Baetz BW, Liu L, Zhang H, Fenech A, Liu Z (2018) Spatiotemporal changes of China’s carbon emissions. Geophys Res Lett 45(16):8536–8546. https://doi.org/10.1029/2018GL079564
Chen W, Yao L (2024) The impact of digital economy on carbon total factor productivity: A spatial analysis of major urban agglomerations in China. J Environ Manag 351:119765. https://doi.org/10.1016/j.jenvman.2023.119765
Cheng Y, Zhang Y, Wang J, Jiang J (2023) The impact of the urban digital economy on China’s carbon intensity: Spatial spillover and mediating effect. Resour Conserv Recycling 189:106762. https://doi.org/10.1016/j.resconrec.2022.106762
Chu H, Ning Y, Qie X (2023) Measurement and spatial correlation analysis of the development level of the digital economy in the Yangtze River Delta urban agglomeration. Sustainability 15(18):13329. https://doi.org/10.3390/su151813329
Dong F, Hu M, Gao Y, Liu Y, Zhu J, Pan Y (2022) How does digital economy affect carbon emissions? Evidence from global 60 countries. Sci Total Environ 852:158401. https://doi.org/10.1016/j.scitotenv.2022.158401
Dong J, Li C (2022) Structure characteristics and influencing factors of China’s carbon emission spatial correlation network: A study based on the dimension of urban agglomerations. Sci Total Environ 853:158613. https://doi.org/10.1016/j.scitotenv.2022.158613
Gao Y, Gao M (2024) Spatial correlation network of municipal solid waste carbon emissions and its influencing factors in China. Environ Impact Assess Rev 106:107490. https://doi.org/10.1016/j.eiar.2024.107490
Gong W, Zhang Z, Chen L, Ma X, Zhao X, Guo Y (2022) Evolution of an urban network in the Yellow River basin based on producer services. Complexity 2022(1):3667745. https://doi.org/10.1155/2022/3667745
Greckhamer T, Furnari S, Fiss PC, Aguilera RV(2018) Studying configurations with qualitative comparative analysis: Best practices in strategy and organization research. Strateg Organ 16(4):482–495. https://doi.org/10.1177/1476127018786487
Guo F, Wang J, Wang F (2020) Measuring China's digital financial inclusion: Index compilation and spatial characteristics. China Econ Q 19(4):1401–1418
Hao X, Liu P, Deng Y (2024) Joint optimization of operational cost and carbon emission in multiple data center micro-grids. Front Energy Res 12:1344837. https://doi.org/10.3389/fenrg.2024.1344837
Huang J, Jin H, Ding X, Zhang A (2023) A study on the spatial correlation effects of digital economy development in China from a non-linear perspective. Systems 11(2):63. https://doi.org/10.3390/systems11020063
Huang L, Zhang H, Si H, Wang H (2023) Can the digital economy promote urban green economic efficiency? Evidence from 273 cities in China. Ecol Indic 155:110977. https://doi.org/10.1016/j.ecolind.2023.110977
Huggins R, Thompson P (2014) A network-based view of regional growth. J Econ Geogr 14(3):511–545. https://doi.org/10.1093/jeg/lbt012
Jia X, Liu Q, Feng J, Li Y, Zhang L (2023) The induced effects of carbon emissions for China’s industry digital transformation. Sustainability 15(16):12170. https://doi.org/10.3390/su151612170
Kazemzadeh E, Fuinhas JA, Salehnia N, Koengkan M, Silva N (2023) Assessing influential factors for ecological footprints: a complex solution approach. J Clean Prod 414:137574. https://doi.org/10.1016/j.jclepro.2023.137574
Kwakwa PA, Adjei-Mantey K, Adusah-Poku F (2023) The effect of transport services and ICTs on carbon dioxide emissions in South Africa. Environ Sci Pollut Res 30(4):10457–10468. https://doi.org/10.1007/s11356-022-22863-7
Lei X, Ma Y, Ke J, Zhang C (2023) The non-linear impact of the digital economy on carbon emissions based on a mediated effects model. Sustainability 15(9):7438. https://doi.org/10.3390/su15097438
Li B, Han Y (2023) Policy effects and mechanisms of ecological civilization demonstration area on carbon efficiency in resource-based cities. Ecol Indic 155:111055. https://doi.org/10.1016/j.ecolind.2023.111055
Li K, Zhou Y, Huang X, Xiao H, Shan Y (2024a) Low-carbon development pathways for resource-based cities in China under the carbon peaking and carbon neutrality goals. Environ Sci Pollut Res 31(7):10213–10233. https://doi.org/10.1007/s11356-023-28349-4
Li Y, Yang X, Ran Q, Wu H, Irfan M, Ahmad M (2021) Energy structure, digital economy, and carbon emissions: evidence from China. Environ Sci Pollut Res 28:64606–64629. https://doi.org/10.1007/s11356-021-15304-4
Li Z, Chen X, Ye Y, Wang F, Liao K, Wang C (2024b) The impact of digital economy on industrial carbon emission efficiency at the city level in China: Gravity movement trajectories and driving mechanisms. Environ Technol Innov 33:103511. https://doi.org/10.1016/j.eti.2023.103511
Li Z, Yuan B, Bai T, Dong X, Wu H (2024c) Shooting two hawks with one arrow: The role of digitization on the coordinated development of resources and environment. Resour Policy 90:104827. https://doi.org/10.1016/j.resourpol.2024.104827
Liu T, Zhang K (2023) Effects of the digital economy on carbon emissions in China: an analysis based on different innovation paths. Environ Sci Pollut Res 30(32):79451–79468. https://doi.org/10.1007/s11356-023-27975-2
Liu Y, Xie Y, Zhong K (2024a) Impact of digital economy on urban sustainable development: Evidence from Chinese cities. Sustain Dev 32(1):307–324. https://doi.org/10.1002/sd.2656
Liu Y, Zhang X, Shen Y (2024b) Technology-driven carbon reduction: Analyzing the impact of digital technology on China’s carbon emission and its mechanism. Technol Forecast Soc Change 2024:123124. https://doi.org/10.1016/j.techfore.2023.123124
Lyu Y, Wu Y, Wu G, Wang W, Zhang J (2023) Digitalization and energy: How could digital economy eliminate energy poverty in China?. Environ Impact Assess Rev 103:107243. https://doi.org/10.1016/j.eiar.2023.107243
Ma Q, Khan Z, Tariq M, IŞik H, Rjoub H (2022) Sustainable digital economy and trade adjusted carbon emissions: Evidence from China’s provincial data. Econ Res-Ekonomska istraživanja 35(1):5469–5485. https://doi.org/10.1080/1331677X.2022.2028179
Ma Y, Wang S, Zhou C (2023) Can the development of the digital economy reduce urban carbon emissions? Case study of Guangdong Province. Land 12(4):787. https://doi.org/10.3390/land12040787
Medaglia R, Rukanova B, Zhang Z (2024) Digital government and the circular economy transition: An analytical framework and a research agenda. Gov Inf Q 41(1):101904. https://doi.org/10.1016/j.giq.2023.101904
Ozcan B, Apergis N (2018) The impact of internet use on air pollution: Evidence from emerging countries. Environ Sci Pollut Res 25:4174–4189. https://doi.org/10.1007/s11356-017-0825-1
Pan L, Yu J, Lin L (2022) The temporal and spatial pattern evolution of land-use carbon emissions in China coastal regions and its response to green economic development. Front Environ Sci 10:1018372. https://doi.org/10.3389/fenvs.2022.1018372
Pan M, Sun M, Wang L, Tai L (2023a) Fostering sustainability: unveiling the impact of Internet development on carbon emissions in China. Environ Sci Pollut Res 30(53):113674–113687. https://doi.org/10.1007/s11356-023-30390-2
Pan M, Zhao X, Rosak-Szyrocka J, Mentel G, Truskolaski T (2023b) Internet development and carbon emission-reduction in the era of digitalization: where will resource-based cities go?. Resour Policy 81:103345. https://doi.org/10.1016/j.resourpol.2023.103345
Rosenthal SS, Strange WC (2008) The attenuation of human capital spillovers. J Urban Econ 64(2):373–389. https://doi.org/10.1016/j.jue.2008.02.006
Schneider CQ, Wagemann C (2012) Set-theoretic methods for the social sciences: A guide to qualitative comparative analysis. Cambridge University Press
Shao T, Peng T, Zhu L, Lu Y, Wang L, Pan X (2024) China’s transportation decarbonization in the context of carbon neutrality: A segment-mode analysis using integrated modelling. Environ Impact Assess Rev 105:107392. https://doi.org/10.1016/j.eiar.2023.107392
Sun B, Fang C, Liao X, Guo X, Liu Z (2023) The relationship between urbanization and air pollution affected by intercity factor mobility: A case of the Yangtze River Delta region. Environ Impact Assess Rev 100:107092. https://doi.org/10.1016/j.eiar.2023.107092
Sun T, Di K, Shi Q (2024a) Digital economy and carbon emission: The coupling effects of the economy in Qinghai region of China. Heliyon 10:e26451. https://doi.org/10.1016/j.heliyon.2024.e26451
Tan S, Li W, Liu X, Wang Y, Wang M (2024) Exploring paths underpinning the implementation of municipal waste sorting: Evidence from China. Environ Impact Assess Rev 106:107510. https://doi.org/10.1016/j.eiar.2024.107510
Tang L, Lu B, Tian T (2021) Spatial correlation network and regional differences for the development of digital economy in China. Entropy 23(12):1575. https://doi.org/10.3390/e23121575
Tapscott D (1996) The digital economy: Promise and peril in the age of networked intelligence. New York: Mc Graw-Hill
Tucker C (2019) Digital data, platforms and the usual [antitrust] suspects: Network effects, switching costs, essential facility. Rev Ind Organ 54(4):683–694. https://doi.org/10.1007/s11151-019-09693-7
Wang H, Yang G, Yue Z (2023a) Breaking through ingrained beliefs: revisiting the impact of the digital economy on carbon emissions. Human Soc Sci Commun 10(1):1–13. https://doi.org/10.1057/s41599-023-02126-7
Wang J, Du F, Xiao F (2023b) Spatial evolution of new infrastructure and its determinants: A case study of big data centers[J]. Acta Geogr Sin 78(2):259–272
Wang X, Zhong M (2023) Can digital economy reduce carbon emission intensity? Empirical evidence from China’s smart city pilot policies. Environ Sci Pollut Res 30(18):51749–51769. https://doi.org/10.1007/s11356-023-26038-w
Wang Z, Liu Q, Xu J, Fujiki Y (2020) Evolution characteristics of the spatial network structure of tourism efficiency in China: A province-level analysis. J Destin Mark Manag 18:100509. https://doi.org/10.1016/j.jdmm.2020.100509
Wei X, Jiang F, Yang L (2023) Does digital dividend matter in China’s green low-carbon development: Environmental impact assessment of the big data comprehensive pilot zones policy. Environ Impact Assess Rev 101:107143. https://doi.org/10.1016/j.eiar.2023.107143
Whichard C, Schaefer DR, Kreager DA (2022) Charting the hidden City: Collecting prison social network data. Soc Netw 69:170–179. https://doi.org/10.1016/j.socnet.2019.09.005
Xie X, Fu H, Zhu Q, Hu S (2024) Integrated optimization modelling framework for low-carbon and green regional transitions through resource-based industrial symbiosis. Nat Commun 15(1):3842. https://doi.org/10.1038/s41467-024-48249-6
Xu Q, Dong Y, Zhong M (2024) Analysis of spatial correlation network of urban digital economy in China. Inf Technol Dev 1–23. https://doi.org/10.1080/02681102.2024.2423393
Xue D, Liu T, Li X, Zhao X (2023) Can the digital economy accelerate “carbon neutrality”?—An empirical analysis based on provincial data in China. Sustainability 15(14):11441. https://doi.org/10.3390/su151411441
Yan X, Zhang Y (2023) Empirical study on the impact of digital economy on carbon emission intensity–based on the mediating role of technological innovation. Front Energy Res 11:1300158. https://doi.org/10.3389/fenrg.2023.1300158
Yang J, Zhang M (2021) The value of entrepreneurship and the entrepreneurial ecosystem: Evidence from 265 cities in China. Growth Change 52(4):2256–2271. https://doi.org/10.1111/grow.12543
Yang L, Lin Y, Zhu J, Yang K (2023) Dynamic coupling coordination and spatial–temporal analysis of digital economy and carbon environment governance from provinces in China. Ecol Indic 156:111091. https://doi.org/10.1016/j.ecolind.2023.111091
Zhang L, Mu R, Zhan Y, Yu J, Liu L, Yu Y, Zhang J (2022a) Digital economy, energy efficiency, and carbon emissions: Evidence from provincial panel data in China. Sci Total Environ 852:158403. https://doi.org/10.1016/j.scitotenv.2022.158403
Zhang W, Wang B, Wang J, Wu Q, Wei YD (2022b) How does industrial agglomeration affect urban land use efficiency? A spatial analysis of Chinese cities. Land Use Policy 119:106178. https://doi.org/10.1016/j.landusepol.2022.106178
Zhang X, Wu X, Zhou W, Fu N (2024) Research on the green innovation effect of digital economy network–Empirical evidence from the manufacturing industry in the Yangtze River Delta. Environ Technol Innov 34:103595. https://doi.org/10.1016/j.eti.2024.103595
Zhao L, Li F, Wang D(2023) How to achieve the common developments of green finance and clean energy in China? Evidence from coupling coordination evaluation. Ecol Indic 155:111011. https://doi.org/10.1016/j.ecolind.2023.111011
Zhou X, Zhou D, Wang Q (2018) How does information and communication technology affect China’s energy intensity? A three-tier structural decomposition analysis. Energy 151:748–759. https://doi.org/10.1016/j.energy.2018.03.115
Zhu H, Zhang D, Goh HH, Wang S, Ahmad T, Mao D, Liu T, Zhao H, Wu T (2023) Future data center energy-conservation and emission-reduction technologies in the context of smart and low-carbon city construction. Sustain Cities Soc 89:104322. https://doi.org/10.1016/j.scs.2022.104322
Zhu Y, Lu S (2024) Digital economy and carbon neutrality: Exploring the pathways and implications for China’s sustainable development. J Knowl Economy 1–18. https://doi.org/10.1007/s13132-024-01931-y
Acknowledgements
This work was supported by the Program of National Natural Science Foundation of China (42130510, 42401217), Shanghai Philosophy and Social Sciences Planning Project (2021BJL002) and the Scientific Research Development Fund from Zhejiang A&F University (2025LFR061).
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SW: conceptualization, methodology, data curation, visualization, writing—original draft, writing—review and editing, funding acquisition. TT: conceptualization, supervision, writing—original draft, funding acquisition. JZ: conceptualization, data curation, writing—review and editing. TL: methodology, data curation, writing—review and editing. ZC: data curation, visualization, writing—review and editing.
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Wang, S., Teng, T., Zhang, J. et al. How does the digital economy affect carbon emissions in China? An analysis based on the perspective of the “space of flows”. Humanit Soc Sci Commun (2026). https://doi.org/10.1057/s41599-025-06417-z
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DOI: https://doi.org/10.1057/s41599-025-06417-z
