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Research on the Impact of Digital Intelligence on Coordinated Regional Development: Causal Inference Based on Double Machine Learning
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Yanting Yao, Jintao Wan
Journal of Technology Economics | 2026, 45(4) : 15 - 26
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Journal of Technology Economics | 2026, 45(4): 15-26
• Industrial Technology Economics •
Research on the Impact of Digital Intelligence on Coordinated Regional Development: Causal Inference Based on Double Machine Learning
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Yanting Yao, Jintao Wan
Affiliations
  • School of Management, Northwest University of Political Science and Law, Xi'an 710122, China
Published: 2026-04-25 doi: 10.12404/j.issn.1002-980X.J25110712
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Digital intelligence, as a core driving force leading the new round of scientific and technological revolution and industrial transformation, is regarded as an important lever for promoting coordinated regional development. Based on panel data from 279 Chinese cities spanning the period from 2011 to 2023, the impact effects and underlying mechanisms of digital intelligence on coordinated regional development were empirically examined using a double machine learning model. It is found that digital intelligence significantly promotes coordinated regional development, and this overall effect is notably stronger than the individual effects of digitalization or intelligence alone. Mechanism tests reveal that digital intelligence indirectly facilitates coordinated regional development by enhancing regional innovation capacity and optimizing regional industrial structures. Moderating effect analysis indicates that government intervention contributes to mitigating the digital divide, thereby strengthening the positive effect of digital intelligence on coordinated regional development. Heterogeneity tests demonstrate that the promotional effect of digital intelligence is influenced by geographical conditions and socioeconomic development levels, and it is found to be more pronounced in the eastern region, the western region, and areas with relatively lower levels of economic development. Further analysis shows that digital intelligence not only promotes overall regional economic growth but also helps narrow the development gap between "core" and "peripheral" cities. The above study reveals the internal logic of empowering coordinated regional development through digital and intelligent transformation, providing empirical evidence and policy references for advancing such transformation in a context-specific manner, optimizing government regulation methods, and addressing regional development imbalances. It holds significant theoretical value and practical implications for achieving high-quality regional economic development.

digital intelligence  /  coordinated regional development  /  regional innovation capacity  /  regional industrial structure  /  government intervention  /  double machine learning
姚延婷, 万进陶. 数智化对区域协调发展的影响研究——基于双重机器学习的因果推断. 技术经济, 2026 , 45 (4) : 15 -26 . DOI: 10.12404/j.issn.1002-980X.J25110712
Yanting Yao, Jintao Wan. Research on the Impact of Digital Intelligence on Coordinated Regional Development: Causal Inference Based on Double Machine Learning[J]. Journal of Technology Economics, 2026 , 45 (4) : 15 -26 . DOI: 10.12404/j.issn.1002-980X.J25110712
Year 2026 volume 45 Issue 4
27
3
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doi: 10.12404/j.issn.1002-980X.J25110712
  • Receive Date:2025-11-07
  • Online Date:2026-10-28
  • Published:2026-04-25
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  • Received:2025-11-07
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    School of Management, Northwest University of Political Science and Law, Xi'an 710122, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
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Percentage of
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属
Genus
种数
Number of
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Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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