PROGRESS IN GEOGRAPHY ›› 2016, Vol. 35 ›› Issue (10): 1206-1217.doi: 10.18306/dlkxjz.2016.10.004

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Spatiotemporal changes and influencing factors of innovation capacity in China

Chunguang HOU(), Yu CHENG, Jianlan REN*(), Yanbin CHEN   

  1. College of Geography and Environment Sciences, Shandong Normal University, Jinan 250014, China
  • Online:2016-10-28 Published:2016-10-26
  • Contact: Jianlan REN;
  • Supported by:
    National Natural Science Foundation of China, No.41501124, No.41571525;National Natural Science Foundation of Shandong Province, No;ZR2015DQ008;Science and Technology Plan Program of Colleges and Universities in Shandong Province, No.J15LH07


Supporting national development by innovation is China's inevitable choice in the new normal economic development environment. In this study, the data of innovation capacity of 30 provinces (municipalities, autonomous regions) from 2000 to 2014 were selected to construct panel datasets, and linear weighted synthesis method, coefficient of variation, Gini coefficient, spatial autocorrelation, NICH index, and macro analysis method, combined with GIS spatial analysis and SPSS data analysis tools were used to explore the spatiotemporal change and influencing factors of innovation capacity in China. The results shows that: (1) In 2000-2014, innovation capacity in China increased year by year, from 0.199 in 2000 to 1.775 in 2014. Knowledge innovation capacity and technology innovation capacity improved faster as compared to government support and service capacities and the basic environment of innovation. (2) Difference in regional innovation capacity shifted from great gap at an overall low capacity level to small gap at and overall high capacity level. High capacity and faster growing areas are mainly concentrated in Shanghai, Jiangsu, Zhejiang, Guangzhou, and other eastern coastal provinces (municipalities). Guizhou, Yunnan, Gansu, Xinjiang, Inner Mongolia, and other provinces (municipalities, autonomous regions) in the southwestern and northwestern regions have relatively low level of innovation capacity and slow growth. (3) Regional material wealth concentration, regional intellectual capital agglomeration, regional innovation environment, and global knowledge spillover are the main factors that affect the change of China's innovation capacity. The research results provide some guidance for the improvement of China's innovation capacity and regional sustainable development.

Key words: innovation geography, innovation capacity, spatiotemporal pattern, spatial autocorrelation, influencing factor, China