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Regional Science & Technology and Innovation

Analysis of Regional Innovation Growth and Catch-up Capability  in China 

—Based on the Meta-frontier Super-efficiency SBM-Malmquist Model 

Tang Zhu, Qin Jiangtao

(School of Management, University of Shanghai for Science and Technology, Shanghai 200093, China)

Abstract: In today's society, we are entering a new era where innovation has become the pri⁃ mary driving force behind economic development. Analyzing the levels of innovation efficiency  and the development potential of different regions is crucial for economic growth and effective re⁃ source allocation. This paper utilizes data from 30 provinces, cities, and districts in China, cover⁃ ing the years from 2013 to 2022. The study begins by dividing the innovation process into two  stages: innovation research and achievement transformation. The regions are categorized into  high-level and low-level groups based on four environmental variables: financial support, the  level of industrial structure optimization, economic development level, and marketization level. The super-efficiency SBM-Malmquist model is used to measure innovation efficiency and exam⁃ ine the trends of the two innovation process groups. This analysis aims to evaluate the capacity for innovation growth. At the same time, the Meta-frontier model is used to assess the innovation  catch-up capability of different regions and to analyze how different environmental factors im⁃ pact innovation efficiency. The results indicate the following: ①All four environmental factors  can promote the growth of innovation efficiency and catch-up capability, but the impact of indus⁃ trial structure optimization is not as significant as that of the other three environmental factors. ② In the innovation research stage, both the high and low groups exhibit growth effects driven pri⁃ marily by MTC under different environmental factors. In the achievement transformation stage, neither group shows growth effects, mainly due to low MEC, with the high group showing more  pronounced challenges in this regard. ③The overall catch-up capability of the high group is bet⁃ ter than that of the low group and the high group shows catch-up effects in both stages. However, this is mainly driven by FCU, while the performance of PTCU is not significantly different from  that of the low group; The low group does not show a catch-up effect in either the innovation re⁃ search stage or the achievement transformation stage, but it exhibits a stronger sustained catchup capability to the high group. ④Compared with the innovation research stage, in the achieve⁃ ment transformation stage, the growth and catch-up capabilities of most regions have signifi⁃ cantly declined in the achievement transformation stage compared to the innovation research  stage. More than half of the regions show neither growth nor catch-up effects, mainly due to the  squeezing of "remaining achievements" that lead to a decrease in technological efficiency and  pure technological efficiency catch-up. Finally, based on the above conclusions, targeted devel⁃ opment and improvement suggestions are proposed from three aspects: first, how to improve pure  technical efficiency and technological progress levels for regions with different levels of develop⁃ ment; second, how to enhance the growth or catch-up capabilities of regions with differing poten⁃ tial for advancement; third, how to address the issue of a significant decline in efficiency in the  achievement transformation stage following high efficiency in the innovation research stage  caused by "residual achievements". 

Key words: catch-up capability; growth capability; innovation efficiency; meta-frontier; Malmquist index