RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2016, Vol. 25 >> Issue (02): 199-207.doi: 10.11870/cjlyzyyhj201602004

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THE TEMPORAL AND SPATIAL EVOLUTION OF CITY INNOVATION DIFFERENCES IN URBAN AGGLOMERATION IN THE MIDDLE REACHES OF THE YANGTZE RIVER

XIAO Gang1,2, DU De-bin1, Li Heng1, DAI Qi-wen3   

  1. 1. East China Normal University, Institute for Innovation and Strategic Studies, Shanghai 200062, China;
    2. Economics Management School of Nanchang University, Nanchang 330031, China;
    3. East China Normal University, The Center of Modern Chinese City Studies, Shanghai 200062, China
  • Received:2015-05-13 Revised:2015-06-26 Online:2016-02-20
  • Supported by:
    the National Natural Science Foundation of China (41471108);The soft science research program of Shanghai science and technology development fund (15692180300)

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Abstract: This research was conducted to analyze the evolution of the spatial and temporal pattern in Middle Yangtze River urban agglomeration from 2000 to 2014, using the amount of patent applications as Geographic Concentration Index and Markov chains method from the perspective of time, space and geographical proximity. The study finds out (1) Differences of city innovation in urban agglomeration indicate the tendency that innovation occurrence shifts from highly concentrated to the gradual dispersion, from the core cities to the peripheral city. They also indicate the tendency that there exists high- and low-level convergence reinforcement lock, accompanied with local variation in middle level cities city club convergence; (2) the shift of city innovation patterns in urban agglomeration is correlated with the development levels of city innovation. The narrower the gap between the development levels of city innovation is, the greater probability of shift is, and vice versa; (3) the neighbor Innovative environment has an influence on the temporal and spatial evolution of city innovation differences in urban agglomeration. The geographical proximity effect is not obvious at low and middle level of city innovation type, while it increases significantly at middle and high level.

Key words: urban agglomeration in the middle reaches of the Yangtze River, spatial Markov chain, city innovation development differences, temporal pattern

CLC Number: 

  • K915
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