Can regional collaborative innovation improve innovation efficiency? An empirical study of Chinese cities

By Fei Fan, Huang Lian, Song Wang. 2020

179 citations recorded by the source corpus.

The relationship between collaborative innovation and innovation efficiency has attracted the attention of researchers in recent years. However, few studies have integrated intra-regional and inter-regional collaborative innovations (IRCI) into a unified framework to analyze the overall impact of regional innovation efficiency. To fill this gap, this paper uses an improved Data Envelopment Analysis Model to measure the innovation efficiency of Chinese cities from 2003 to 2016 based on the regional innovation capability. Using the Coupling Coordination Degree Model to measure the degree of intra-regional collaborative innovation, we constructed a Capability Structure Model to measure the degree of IRCI, then used the Spatial Durbin Model to empirically analyze the influence of intra-regional and IRCI on regional innovation efficiency. The results show that: (a) both intra-regional and IRCI promote regional innovation efficiency, but the internal factors are the primary influences on regional innovation efficiency; (b) intra-regional collaborative innovation not only promotes local regional innovation efficiency but also promotes innovation efficiency in other regions effectively, although its driving effect on the local region is higher than on other regions; (c) there is a time lag in promoting regional innovation efficiency through the cooperation and interaction among innovation in knowledge, technological, industrial, and service, and environment capabilities. The regional innovation capacities can result in good collaborative innovation effects only after a certain period of cooperation.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/70c9f835caac13f7656cf31724360adc9560a141

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Citations in the corpus

• Innovation agglomeration and urban hierarchy: evidence from Chinese cities (2021, background): “As the C-D production function is characterized by a convenient increase and decrease of variables, the knowledge production function is in the form of the C-D production function (Fischer 2002).”