RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2022, Vol. 31 >> Issue (4): 770-780.doi: 10.11870/cjlyzyyhj202204005

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Research on the Dynamic Evolution and Driving Factors of Spatial Agglomeration of Knowledge-intensive Services

HUO Peng1,2   

  1. (1. Social Service and Development School, Zhengzhou Normal University, Zhengzhou 450044, China;2.Business School, Henan University, Kaifeng 475004, China)
  • Online:2022-04-20 Published:2022-04-21

Abstract: Knowledge intensive service industry is an important part of China’s modern independent innovation system. This paper explores the dynamic evolution trend of spatial agglomeration of knowledge-intensive services in prefecture-level and above cities in China by constructing a comprehensive measurement model, and reveals the driving factors of spatial agglomeration of knowledge-intensive services by using geographically weighted regression model. The results show that:(1) The overall degree of knowledge-intensive service industry agglomeration in China is low, the industrial agglomeration is not sufficient, the regional agglomeration is not balanced, and the agglomeration trend of different subsectors is obviously different. The spatial agglomeration trend is gradually developing towards the eastern coastal region as the center, and the central and western regions as the periphery; (2) The agglomeration of knowledge-intensive service industry has obvious positive spatial autocorrelation, and the agglomeration of knowledge-intensive service industry in the neighboring area has strong mutual driving effect; (3) the system of urbanization level, research and development strength, environmental factors, the stock of knowledge, on the whole, are an important force in driving knowledge intensive service industries agglomeration, based on the analysis of the spatial heterogeneity, knowledge-intensive service industry spatial agglomeration driving factors on the varied impact of different areas, on the whole present obvious ladder distribution characteristics, The spatial distribution characteristics of the elasticity coefficients of variables in adjacent provincial capitals or municipalities are significant, and the spatial spillover effect of agglomeration driving factors is obvious.

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