Uncovering the evolution of digital economy investment networks: a county-level perspective

Abstract The digital economy drives economic growth and regional competitiveness. Understanding the evolution of county-level digital economies is essential for regional economic transformation, upgrading, and long-term development. Traditional assessment methodologies have several shortcomings for representing the county digital economy, especially data availability and reliability. In this paper, we develop a multi-scale analytic framework using complex network indicators including average clustering coefficient, $$k$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>k</mml:mi> </mml:math> -core, and weighted degree at macro, meso, and micro scales. The framework allows us to establish a county-level network using enterprise investment data from Fujian Province, China, to study digital economy investment development from 2000 to 2021. The outcomes are: 1) The digital economy's investment scale and connection in the county grew in stages, with network expansion aligning with the concept of"the rich leading the whole, and the whole leading the poor."2) The interconnectivity hot zones, which made up less than 9% of counties, had a major impact on the network and have gotten stronger. Investment linkage control increased from 24.64% in 2000 to 41.56% in 2021, and the focus of hot areas shifted from outside the province to within the province. 3) Over time, the top six key counties have increasingly controlled more than 30% of the total investment quota. In 2021, when 2% of counties controlled 60% of investment, developmental imbalances became more important.

Authors

Institutions

Publication Details

Journal
Computational Urban Science
Published
2025-04-11
DOI
https://doi.org/10.1007/s43762-025-00179-9
Citations
1
Primary Topic
ICT Impact and Policies
Type
article
Field-Weighted Citation Impact
1.14

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Uncovering the evolution of digital economy investment networks: a county-level perspective

Daichao Li, Fenghua Xie, Yang Xu, Peng Peng et al.
1 citations
Computational Urban Science
ICT Impact and Policies
1.14
article

Uncovering the evolution of digital economy investment networks: a county-level perspective

Daichao Li, Fenghua Xie, Yang Xu, Peng Peng, Mingzhen Wu
article en
1 citations

Abstract

Abstract The digital economy drives economic growth and regional competitiveness. Understanding the evolution of county-level digital economies is essential for regional economic transformation, upgrading, and long-term development. Traditional assessment methodologies have several shortcomings for representing the county digital economy, especially data availability and reliability. In this paper, we develop a multi-scale analytic framework using complex network indicators including average clustering coefficient, $$k$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>k</mml:mi> </mml:math> -core, and weighted degree at macro, meso, and micro scales. The framework allows us to establish a county-level network using enterprise investment data from Fujian Province, China, to study digital economy investment development from 2000 to 2021. The outcomes are: 1) The digital economy's investment scale and connection in the county grew in stages, with network expansion aligning with the concept of"the rich leading the whole, and the whole leading the poor."2) The interconnectivity hot zones, which made up less than 9% of counties, had a major impact on the network and have gotten stronger. Investment linkage control increased from 24.64% in 2000 to 41.56% in 2021, and the focus of hot areas shifted from outside the province to within the province. 3) Over time, the top six key counties have increasingly controlled more than 30% of the total investment quota. In 2021, when 2% of counties controlled 60% of investment, developmental imbalances became more important.

Computational Urban ScienceVol. 5(1)
Chinese Academy of Sciences (CN), Fujian Academy of Building Research (China) (CN), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN), Xi’an Jiaotong-Liverpool University (CN), Fuzhou University (CN)
Fujian Provincial Department of Science and Technology, National Key Research and Development Program of China
Openalex Percentile: Top 21%
ICT Impact and Policies
1.14
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.