Study On Spatial Distribution Of Urban Innovation Capacity And Its Influencing Factors

General Secretary Xi Jinping emphasized the importance of innovation on many occasions in the Party's Nineteenth National Congress report.Innovation is the primary driving force for development,urban innovation capability is a decisive factor for regional economies to gain competitive advantage and plays a decisive role in regional development.Therefore,it is of great significance to explore the characteristics of urban innovation capabilities and promote strategies in a new perspective.This study first summarized the relevant literature at home and abroad and gave a review of the current research status.To better understand the concept of urban innovation capability,the theoretical basis of urban innovation capability was also reviewed.On this basis,a theoretical analysis framework was constructed to determine the city's innovation capability and its measurement indicators.Then,using the patent application authorization data and related economic data of 285 prefecture-level and above cities in China in 2016.A global and local spatial autocorrelation test of urban innovation output agglomeration was conducted using the Exploratory Spatial Data Analysis method(ESDA).According to the test results,the Confirmatory Spatial Data Analysis method(CSDA)was adopted.The Spatial Lag Model(SLM),Spatial Error Model(SEM)and Ordinary Least Squares model(OLS)were compared and tested,and the influencing factors of China's urban innovation capacity were spatially analyzed.Finally,the main empirical results were summarized,and related optimization countermeasures were given according to the influencing factors of China's urban innovation capability.The research results show that the layout of China's urban innovation output not only has overall spatial autocorrelation,but also has local spatial correlation.On this basis,the influencing factors of urban innovation capacity are analyzed in depth.It is found that the spatial econometric model is more accurate and scientific than the Ordinary Least Squares(OLS)model estimation.Urban innovation has a significant spillover effect on neighboring space,which means Spatial Lag Model(SLM)is more appropriate than Spatial Error Model(SEM).The analysis of the influencing factors shows that the institutional factors,openness to the outside world,economic basis,R&D investment,and informationization degree have all passed the significant test.The institutional factors,economic basis,R&D investment,and informationization degree have positive effects.The degree of opening to the outside world is consistent with the estimation in the Ordinary Least Squares(OLS)model and shows a negative effect.R&D investment and economic fundamentals have the greatest impact,institutional factors need to be improved,and the degree of informationization is expected to play an increasingly important role in the future.Combining the statistical analysis results with the actual situation of urban innovation in China,this study proposes optimization measures from six aspects,including exerting government initiative,enhancing economic strength,increasing R&D investment,strengthening information construction,optimizing opening to the outside world,and promoting regional coordinated development.