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Dynamic Evolution, Spatial Differences, and Driving Factors of China’s Provincial Digital Economy

Author

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  • Run Luo

    (School of Geography Science, Nanjing Normal University, Nanjing 210023, China)

  • Nianxing Zhou

    (School of Geography Science, Nanjing Normal University, Nanjing 210023, China
    Jiangsu Center of Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China)

Abstract

The digital economy is critical to national economic growth and high-quality economic development. It is theoretically and practically significant to measure the development level and spatial differences in the digital economy to promote the construction of a digital China. This study constructed a digital economy evaluation index and analyzed the dynamic evolution, spatial differences, and driving factors of China’s provincial digital economy from 2011 to 2020 using a spatial Markov chain, the Dagum Gini coefficient, and geographical detector methods. The results demonstrated that China’s provincial digital economy grew from 2011 to 2020. The spatial distribution of the digital economy was high in eastern provinces and municipalities such as Beijing, Shanghai, Guangdong, Jiangsu, and Zhejiang, and low in central and western provinces and autonomous regions. The probability of upward transfer in developing China’s provincial digital economy was greater than that of preserving the original state, and China’s provincial digital economy has great potential for development. A region with a medium-high level in the digital economy is more likely to achieve high-level development when neighboring regions are characterized by a medium-high or high level of digital economy development, as the spillover effects from the neighbors may be strongly favorable and the region takes advantage of its developed surroundings. There were significant spatial differences in the development of China’s provincial digital economy, caused primarily by inter-regional differences. The spatial differentiation of China’s provincial digital economy was caused by the interaction of multiple factors, led by economic conditions and R&D expenditure.

Suggested Citation

  • Run Luo & Nianxing Zhou, 2022. "Dynamic Evolution, Spatial Differences, and Driving Factors of China’s Provincial Digital Economy," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9376-:d:877045
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    References listed on IDEAS

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    Cited by:

    1. Xiaoting Shang & Huayong Niu, 2023. "Analysis of the Spatiotemporal Evolution and Driving Factors of China’s Digital Economy Development Based on ESDA and GM-GWR Model," Sustainability, MDPI, vol. 15(15), pages 1-21, August.
    2. Ye Tian & Qin Liu & Yiting Ye & Zhaofang Zhang & Ribesh Khanal, 2023. "How the Rural Digital Economy Drives Rural Industrial Revitalization—Case Study of China’s 30 Provinces," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
    3. Congqi Wang & Rui Zhang & Haslindar Ibrahim & Pengzhen Liu, 2023. "Can the Digital Economy Enable Carbon Emission Reduction: Analysis of Mechanisms and China’s Experience," Sustainability, MDPI, vol. 15(13), pages 1-20, June.
    4. Jinkai Liang & Ke Du & Dandan Chen, 2023. "The Effect of Digitalization on Ambidextrous Innovation in Manufacturing Enterprises: A Perspective of Empowering and Enabling," Sustainability, MDPI, vol. 15(16), pages 1-23, August.
    5. Yunlong Cheng & Jian Yang, 2023. "Spatial and Temporal Divergence in the Coupling Coordination of Digital Economy, Environmental Regulation and Sustainable Development: An Experience Study in China," Sustainability, MDPI, vol. 15(12), pages 1-16, June.
    6. Jianing Xu & Weidong Li, 2022. "The Impact of the Digital Economy on Innovation: New Evidence from Panel Threshold Model," Sustainability, MDPI, vol. 14(22), pages 1-19, November.

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