Analysis of spatial patterns of technological innovation capability based on patent data in Jiangsu province, China

Abstract

AbstractInnovation is the main driver of regional economic development. Exploring the spatial patterns of regional innovation can elucidate the regional differences in innovation development. Nearly all the researches on spatial patterns of innovation take the administrative divisions of provinces, cities and counties as spatial units, and portray the spatial patterns of regional innovation from the macroscopic overall, but lack the spatial patterns within the regions. This paper employed patents of Jiangsu province, China in 2019 as a sample, divided the spatial units based on geographic coordinates of patent data, calculated the technological innovation capability index of within the spatial units, overcoming the drawbacks of the research method that fails to reveal the internal pattern of cities by using provinces, cities and counties as the research scale, and analysed the spatial patterns of technological innovation capability in Jiangsu province by using spatial autocorrelation analysis and standard deviation ellipse. The results show that: (1) In terms of distribution, the spatial pattern of technological innovation capability in Jiangsu province is obviously “one core and one belt” in southern Jiangsu, with Nanjing as the core and Suzhou, Wuxi and Changzhou as a southeast-northwest belt of high innovation capacity, while multi-point scattered in northern Jiangsu. (2) From the perspective of aggregation mode, each city has the largest number of H-H agglomeration units, relatively presenting a zonal distribution in the Suzhou-Wuxi-Changzhou area and Nanjing, and less distribution in other places. (3) Industrially speaking, the development of technological innovation capability of the secondary industry in many cities is better and centralized, while secondary and tertiary industries move hand in hand around the city centre in Nanjing, and the tertiary industry dominates comparably in Suzhou and Wuxi.