Research on the Influencing Factors of China's Industrial Agglomeration Level Based on Configuration Perspective

Xinyu Hu

doi:10.54097/bhz3cy95

Authors

Xinyu Hu

DOI:

https://doi.org/10.54097/bhz3cy95

Keywords:

Industrial Agglomeration Level, Configuration Perspective, Influencing Factors, Fuzzy-Set Qualitative Comparative Analysis.

Abstract

With the development of Internet and artificial intelligence, the level of industrial agglomeration has gradually become the top priority to competitiveness. This study uses the fuzzy-set qualitative comparison analysis (fsQCA), based on the configuration perspective. Based on the cross-sectional data of 31 provinces in 2023, the conditional configuration path of high industrial agglomeration level (CYJJSP) is constructed. And the influence of six main factors on CYJJSP is analyzed, which are economic development level, government intervention degree, regional innovation level, industrial structure, transportation development level, and human capital. The study shows that: First, none of the six single antecedent conditions is necessary for high CYJJSP, but it is helpful to achieve high CYJJSP in general. Secondly, high CYJJSP needs multi-condition linkage mechanism to achieve, and two configuration paths are obtained after processing data. The configuration is tested for robustness by changing the threshold or consistency, and the configuration is still stable after the test. Finally, by comparing the two configuration paths, it is found that there is an obvious substitution relationship between the condition combinations. The study explores the effect of each factor, which not only enriches the theoretical framework for achieving high CYJJSP, but also provides practical guidance for high CYJJSP.

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References

[1] Yang Haiqing, He Yong. Nondestructive variety discrimination of fragrant mushrooms based on Vis/NIR spectral analysis [C]. CISP: FIRST INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING,2008,4:64-67.

[2] Tang Xiaohua, Li Jingwen. Fiscal decentralization, Distortion Effect and Manufacturing industry Agglomeration [J]. Journal of Southwest University for Nationalities,2021,42 (04):146-154.

[3] Qiao, Yanyun, He, Jingjing. The Impact of Smart City Construction on Carbon Emission Levels [J]. Chinese Social Science Series,2023,5 (2):142-184.

[4] Zhang Luo, Gao Peng. Spatial Effects of Higher Vocational Education on Industrial Agglomeration [J]. Heilongjiang Higher Education Research, 2024,42 (05):52-59.

[5] Wei Heqing, Li Ying, Spatial Characteristics and Influencing Factors of Provincial Cultural Industry Agglomeration in China [J].Statistics and Decision, 2021,37 (16):66-70.

[6] Cheng, Hu, Man, Lee Sang. A Study on the Socio-Economic Benefits of Collective Zone of Cultural and Creative Industries in Urban Renewal -A Case Study of Guangzhou-[J]. Korean-Chinese Social Science Studies,2021,19 (1):192-207.

[7] Xu, jin, Song Yu, Gao Yang. Evolution Trend and Influence Factors of TFP of Chinese Regional Manufacturing [J]. Korean-Chinese Social Science Studies, 2016,14 (1): 415-442.

[8] You Ruiling. Institutional Quality and High-tech Industry Agglomeration: An Empirical Study based on Panel Threshold Model [J].Research on Technology, Economics and Management,2020, (11):10-15.

[9] Xu Shidao, Jiang Jing, Zheng Jie. Has the national high-tech Zone been established to promote industrial collaborative agglomeration? -- Empirical test based on difference-difference method [J]. Exploration of economic issues, 2022, (11):113-127.

[10] Feng, Wei, Lee, Hyukku. Research on the Impact of China's Environmental Regulations on Industrial Agglomeration[J]. The Journal of Northeast Asian Economic Studies,2022,34 (1):63-86.

[11] Wu, Jianjun, Yu, Xiuling, Malik, Zaffar, Chen, Hao, Xu, Jianming. Impacts of Copper on Rice Growth and Yield as Affected by Pig Manure [C]. MOLECULAR ENVIRONMENTAL SOIL SCIENCE AT THE INTERFACES IN THE EARTH'SCRITICALZONE,2010,141-143.

[12] Tang Yingxia, Liu Yong. Analysis on TianJin Municipality's Culture Industry Development and Existing Problems [J]. Korean-Chinese Social Science Studies, 2013,11 (1):311-344.

[13] Xu, jin, Guan, Bohan. A Study on the Competitiveness of Automobile Industry Cluster in the Yangtze River Delta Region [J]. China Knowledge Network, 2019,13 (13):161-194.

[14] Sun Na, Tao Ketao, Yang Shiwei, Chen Wenhui. Evolution characteristics and improvement Strategies of China's digital industry agglomeration level [J].Regional Economic Review,2024, (01):31-42.

[15] Zhang Shushan, Chen Kaixuan, Song Yang. Analysis on Regional differences and convergence of virtual agglomeration level of Chinese urban digital Industry [J].Urban problems, 2024, (10):47-58.

[16] Liu Feng, Liao Xin, Zhou Xianyong. Generation Logic and Realization Path of Urban Business Environment Optimization: Multiple Analysis Based on Fieldwork and QCA [J]. Science and Technology Progress and Countermeasures, 2024,41 (19):46-55.

[17] Wang Yajie, Xin Xiaodan, Wu Yifei, et al. The Path of Digital Economy Driving the Development of Beijing-Tianjin-Hebei Innovation Network [J/OL]. Science of Science and Management of Science and Technology, 2025,1-32 [2025-02-12].

[18] Ji Chun, Chen Yumeng, Gao Chunnan. Study on the Factors and Countermeasures of the Transformation of Scientific and Technological Achievements in Universities—a Case Study of Universities in Nanjing, Jiangsu Province [J]. Tianjin Science and Technology, 2024, 51 (11): 56-60.