Study on the Measurement of the Level of Development of the Digital Economy and the Structure of Spatial Networks

Authors

  • Yuhong Yang
  • Aiyin Wang
  • Chenchen Liu
  • Chu Chu

DOI:

https://doi.org/10.54097/zxv66p91

Keywords:

Digital Economic Development, Entropy Power Method, Spatial Network Structure, Social Network Analysis

Abstract

Based on the provincial panel data from 2013-2021, the entropy weight method is used to measure the comprehensive development index of the digital economy, and the gravity model and social network analysis are used to examine the spatial correlation network structure characteristics of the digital economy. digital economy, and the gravity model and social network analysis are used to examine the spatial correlation network structure characteristics of the digital economy among provinces and regions. The study found that: (1) the overall digital economy development level of China's provinces and municipalities is on the rise, but the overall digital economy development level of China's provinces and municipalities is not as high as it should be. municipalities is on the rise, but there is a large gap in the level of digital economy development between regions, and the level of development is gradually declining from China's eastern region to the western region; (2) the spatial network structure of China's level of digital economy development has a better robustness, and development has a better robustness, and the spatial correlation on the whole is strengthened, but the speed of development is relatively slow, and at the same time, the spatial network hierarchical structure is more rigid, and regions under different geographic locations and different levels of development are likely to have spatial network hierarchical structure. development is likely to have spatial interaction effects. (3) The distribution pattern of "core-edge" is formed among provinces and regions, with the distribution pattern of "core-edge" is formed among provinces and regions, with Shanghai, Beijing, Sichuan, Anhui, Shandong, Guangdong, Jiangsu, Henan, Zhejiang, Hubei and Shaanxi being at the core of the network, with strong aggregation and radiation ability. The distribution pattern of "core-edge" is formed among provinces and regions, with Shanghai, Beijing, Sichuan, Anhui, Shandong, Jiangsu, Henan, Zhejiang, and Hubei being at the core of the network, with strong aggregation and radiation ability.

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References

Ayres R U, Williams E. The digital economy: Where do we stand? [J]. Technological Forecasting and Social Change, 2004, 71(4): 315-339.

PANG Jian, ZHU Xinmin. Development trend of foreign digital economy and national development strategy of digital economy[J]. Science and Technology Progress and Countermeasures,2013,30(08):124-128.

Kobilov A U, Khashimova D P, Mannanova S G, et al. Modern content and concept of digital economy[J]. International Journal of Multicultural and Multireligious Understanding, 2022, 9(2): 375-378.

Li Changjiang. A preliminary discussion on the connotation of digital economy[J]. E-government,2017(09):84-92.

GONG Xiaoying, YANG Rou. Research on the theoretical logic and realistic path of digital economy development[J]. Contemporary Economic Research,2021(01):17-25+112.

WANG Jun,ZHU Jie,RO Xi. Development level and evolution measurement of China's digital economy[J]. Research on Quantitative and Technical Economics, 2021,38(07):26-42.

ZHANG Hong, DONG Juyuan, WANG Lu. High-quality development of China's digital economy: connotation, current situation and countermeasures[J]. Journal of Humanities, 2022 (10):75-86.

Xiang Shujian,Wu Wenjun. Research on the design of satellite account framework for China's digital economy[J]. Statistical research,2019,36(10):3-16.

YANG Zhongshan, ZHANG Meihui. Satellite accounts for the digital economy: International experience and the design of China's compilation program[J]. Statistical research, 2019, 36 (05):16-30.

HAN Zhao'an, ZHAO Jingfeng, WU Haizhen. A study on the size measurement, non-equilibrium and regional differences of China's inter-provincial digital economy[J]. Research on Quantitative and Technical Economics,2021,38(08):164-181.

ZHU Facang,LE Guanlan,LI Qianqian. Scale measurement of value added of digital economy[J]. Research World, 2021 (02): 56-64.

Wang Jun, Liu Xiaofeng, Zhu Jie. Can digital economy promote the high-quality development of regional economy? [J]. China Soft Science,2023(01):206-214.

Jurayevich M B, Bulturbayevich M B. The impact of the digital economy on economic growth[J]. International Journal on Integrated Education, 2020, 3(6): 16-18.

Sui D Z, Rejeski D W. Environmental impacts of the emerging digital economy: the e-for-environment e-commerce? [J]. Environmental Management, 2002, 29: 155-163.

Deng Rongrong, Zhang Aoxiang. Research on the impact and mechanism of digital economy development on environmental pollution in Chinese cities[J]. Southern Economy,2022(02):18-37.

Zhang Yongheng, Wang Family. Does the development of digital economy reduce the level of factor mismatch in China? [J]. Statistics and Information Forum,2020,35(09):62-71.

Czarniewski S. Quality parameters of human capital in the digital economy[J]. International Journal of Academic Research in Accounting, Finance and Management Sciences, 2014, 4(3): 193-198.

Ogli N S F, Ogli R B O. In The Context of Developing the Digital Economy Modern Forms of Employment[J]. Eurasian Scientific Herald, 2021, 1(1): 11-16.

Qi Yudong, Ding Shulei, Liu Cuihua. Construction of new career development and new labor relations in the era of digital economy[J]. Reform,2021(09):65-81.

Bertani F, Ponta L, Raberto M, et al. The complexity of the intangible digital economy: an agent-based model[J]. Journal of business research, 2021, 129: 527-540.

Hao C, Zhang Shaojie. Research on the evaluation of China's interprovincial ecological data based on entropy value method[J]. Intelligence Science,2021,39(01):157-162.

WANG Kai, GAN Chang, YANG Yaping et al. Evolution of municipal tourism economic network structure and its driving factors in the city cluster in the middle reaches of the Yangtze River[J]. Geography and Geographic Information Science, 2019, 35(05):118-125.

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Published

29-05-2024

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