A comparative analysis of changes in urban innovation spatial correlation effect in China and its driving factors. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Pan, Xiongfeng; Chu, Junhui; Pan, Xianyou; Wang, Mengyang
• Is Part Of: Asian journal of technology innovation. Volume 29:Issue 1(2021)
• Page Start: 1
• Page End: 15
• Publication Date: 2021-01-02
• Subjects: Spatial correlation effect -- urban innovation -- change characteristics -- driving factor -- China; Technological innovations -- East Asia -- Periodicals; Technological innovations -- Southeast Asia -- Periodicals; Technological innovations -- Periodicals; Research, Industrial -- East Asia -- Periodicals; Research, Industrial -- Southeast Asia -- Periodicals; Research, Industrial -- Periodicals; 338.064095
• DOI: 10.1080/19761597.2020.1726782
• Languages: English
• ISSNs: 1976-1597

Abstract

ABSTRACT: On the basis of gravity and potential models combined with GIS spatial analysis method, this paper analyses the change characteristics of the urban innovation spatial correlation effect in China and its driving factors. The main conclusions are as follows: first, the density of urban innovation spatial correlation in China has increased from 1990 to 2014. Beijing, Shanghai, Guangzhou, and Chengdu are the most important node cities in China's urban innovation spatial correlation network. Second, in 1990, seven innovation correlation zones formed around Beijing, Shanghai, Shenyang, Guangzhou, Chengdu, Wuhan, and Xi'an. Among them, Beijing has the largest innovation correlation radiation intensity. In 2014, the innovation correlation intensities of Guangzhou and Shanghai have exceeded that of Beijing. Relying on good scientific research resources and military infrastructure, the innovation correlation intensities of Chengdu, Xi'an and Wuhan is also increase gradually under the guidance of innovation-driven and military-civilian integration strategies. The innovation correlation intensity of Shenyang shows a certain degree of decline because of the rigid mechanism and other reasons. Third, the geographical adjacency and similarity in marketization degree, economic development level, and human capital significantly positively affect the urban innovation spatial correlation and spillover effect.