Measurement and spatiotemporal patterns of China's digital economy efficiency

Yanting Xu; Tinghui Li; Yanting Xu; Tinghui Li

doi:10.3934/math.20231500

AIMS Mathematics

2023, Volume 8, Issue 12: 29307-29331. doi: 10.3934/math.20231500

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Research article Special Issues

Measurement and spatiotemporal patterns of China's digital economy efficiency

Yanting Xu ,
Tinghui Li ^,

School of Economics and Statistics, Guangzhou University, Guangzhou, China

Received: 11 September 2023 Revised: 13 October 2023 Accepted: 22 October 2023 Published: 30 October 2023
MSC : 62P20

The digital economy has deeply integrated into various sectors, becoming a significant driving force for economic transformation and development, as new generation information technology continues to advance and mature. This paper builds upon theoretical analysis and employs the global Data Envelopment Analysis (DEA) method, along with relevant data from China's information transmission, software and information services industry spanning the years 2003 to 2020, to dynamically measure the output efficiency of China's digital economy. Based on this, the paper examines the overall characteristics of efficiency changes in the digital economy using distribution dynamics. Additionally, common descriptive statistics and data mapping techniques are utilized to reveal the spatiotemporal patterns of efficiency changes. The findings of the study are as follows: (1) The efficiency of the digital economy in the 31 provincial regions of China remains stable, but the factors influencing this efficiency vary both over time and among specific provinces. (2) From a temporal perspective, the digital economy in China demonstrates an overall positive increase in efficiency, with its volatility and differentiation largely shaped by the shifting factors of technological advancements and technological efficiency. (3) From a spatial perspective, there exists a distinct pattern of spatial disparities in China's digital economy efficiency, with higher efficiency observed in the eastern regions and lower efficiency in the western regions.
- digital economy efficiency,
- DEA,
- distribution dynamics,
- spatiotemporal patterns,
- data visualization
Citation: Yanting Xu, Tinghui Li. Measurement and spatiotemporal patterns of China's digital economy efficiency[J]. AIMS Mathematics, 2023, 8(12): 29307-29331. doi: 10.3934/math.20231500

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Abstract

The digital economy has deeply integrated into various sectors, becoming a significant driving force for economic transformation and development, as new generation information technology continues to advance and mature. This paper builds upon theoretical analysis and employs the global Data Envelopment Analysis (DEA) method, along with relevant data from China's information transmission, software and information services industry spanning the years 2003 to 2020, to dynamically measure the output efficiency of China's digital economy. Based on this, the paper examines the overall characteristics of efficiency changes in the digital economy using distribution dynamics. Additionally, common descriptive statistics and data mapping techniques are utilized to reveal the spatiotemporal patterns of efficiency changes. The findings of the study are as follows: (1) The efficiency of the digital economy in the 31 provincial regions of China remains stable, but the factors influencing this efficiency vary both over time and among specific provinces. (2) From a temporal perspective, the digital economy in China demonstrates an overall positive increase in efficiency, with its volatility and differentiation largely shaped by the shifting factors of technological advancements and technological efficiency. (3) From a spatial perspective, there exists a distinct pattern of spatial disparities in China's digital economy efficiency, with higher efficiency observed in the eastern regions and lower efficiency in the western regions.

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