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
- Daichao Li (ORCID: https://orcid.org/0000-0003-1702-1564)
- Fenghua Xie
- Yang Xu
- Peng Peng (ORCID: https://orcid.org/0000-0003-2838-2111)
- Mingzhen Wu
Institutions
- 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)
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
- Fujian Provincial Department of Science and Technology
- National Key Research and Development Program of China