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...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Springer
2025-04-01
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| Series: | Computational Urban Science |
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| Online Access: | https://doi.org/10.1007/s43762-025-00179-9 |
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| author | Fenghua Xie Peng Peng Daichao Li Yang Xu Mingzhi Wu |
| author_facet | Fenghua Xie Peng Peng Daichao Li Yang Xu Mingzhi Wu |
| author_sort | Fenghua Xie |
| collection | DOAJ |
| description | 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, $$k$$ k -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. |
| format | Article |
| id | doaj-art-8ab943303e99481d9964e5d6d05b1e1e |
| institution | OA Journals |
| issn | 2730-6852 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Springer |
| record_format | Article |
| series | Computational Urban Science |
| spelling | doaj-art-8ab943303e99481d9964e5d6d05b1e1e2025-08-20T02:12:03ZengSpringerComputational Urban Science2730-68522025-04-015111810.1007/s43762-025-00179-9Uncovering the evolution of digital economy investment networks: a county-level perspectiveFenghua Xie0Peng Peng1Daichao Li2Yang Xu3Mingzhi Wu4The Academy of Digital China (Fujian), Fuzhou UniversityState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of SciencesThe Academy of Digital China (Fujian), Fuzhou UniversityState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of SciencesXi’an Jiaotong-Liverpool UniversityAbstract 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, $$k$$ k -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.https://doi.org/10.1007/s43762-025-00179-9Digital economyNetwork analysisInvestment networkCounty-level scaleMulti-scale |
| spellingShingle | Fenghua Xie Peng Peng Daichao Li Yang Xu Mingzhi Wu Uncovering the evolution of digital economy investment networks: a county-level perspective Computational Urban Science Digital economy Network analysis Investment network County-level scale Multi-scale |
| title | Uncovering the evolution of digital economy investment networks: a county-level perspective |
| title_full | Uncovering the evolution of digital economy investment networks: a county-level perspective |
| title_fullStr | Uncovering the evolution of digital economy investment networks: a county-level perspective |
| title_full_unstemmed | Uncovering the evolution of digital economy investment networks: a county-level perspective |
| title_short | Uncovering the evolution of digital economy investment networks: a county-level perspective |
| title_sort | uncovering the evolution of digital economy investment networks a county level perspective |
| topic | Digital economy Network analysis Investment network County-level scale Multi-scale |
| url | https://doi.org/10.1007/s43762-025-00179-9 |
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