Measurement and prediction of the development level of China’s digital economy

This paper investigates the development level of the digital economy of China. Firstly, an indicator system of the digital economy is constructed from five aspects: digital infrastructure construction, digitalization level of society, growth of the economy promoted by Information and Communication Technologies (ICT), development level of digital economy industries, and capitalization level of digital economy enterprises. Secondly, we use Kullback-Leibler (K-L) divergence and time-difference correlation coefficient to classify the indicators, and construct a prosperity index. Thirdly, this paper establishes Grey-Markov model combining grey system and Markov chain, further uses this model to predict the development level of digital economy. The empirical analysis shows the Grey-Markov model is superior to grey prediction model in capturing random fluctuations, and Monte Carlo simulation indicates that this model has good robustness. It finds that the gradual deceleration of development will make digital economy close to the relatively stagnant period, although its development level remains stable in the next two years. This research will provide theoretical basis of decisions for government departments, and offer strategic support of the digital transformation for enterprises.

Authors

Institutions

Publication Details

Journal
Humanities and Social Sciences Communications
Published
2024-12-31
DOI
https://doi.org/10.1057/s41599-024-04352-z
Citations
9
Primary Topic
Economic and Technological Developments in Russia
Type
article
Field-Weighted Citation Impact
12.62
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Measurement and prediction of the development level of China’s digital economy

Shengjie Lai, Yuexu Zhao, Hao Chen
9 citations
Humanities and Social Sciences Communications
Economic and Technological Developments in Russia
12.62
article

Measurement and prediction of the development level of China’s digital economy

Shengjie Lai, Yuexu Zhao, Hao Chen
article en
9 citations

Abstract

This paper investigates the development level of the digital economy of China. Firstly, an indicator system of the digital economy is constructed from five aspects: digital infrastructure construction, digitalization level of society, growth of the economy promoted by Information and Communication Technologies (ICT), development level of digital economy industries, and capitalization level of digital economy enterprises. Secondly, we use Kullback-Leibler (K-L) divergence and time-difference correlation coefficient to classify the indicators, and construct a prosperity index. Thirdly, this paper establishes Grey-Markov model combining grey system and Markov chain, further uses this model to predict the development level of digital economy. The empirical analysis shows the Grey-Markov model is superior to grey prediction model in capturing random fluctuations, and Monte Carlo simulation indicates that this model has good robustness. It finds that the gradual deceleration of development will make digital economy close to the relatively stagnant period, although its development level remains stable in the next two years. This research will provide theoretical basis of decisions for government departments, and offer strategic support of the digital transformation for enterprises.

Humanities and Social Sciences CommunicationsVol. 11(1)
Hangzhou Dianzi University (CN)
Decent work and economic growth
Openalex Percentile: Top 1%
Economic and Technological Developments in Russia
12.62
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.