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| Innovation Efficiency Measurement,Regional Difference and Spatial Convergence of High-tech Digital Manufacturing Industry |
| Zhang Yuanqing1,2,Liu Shuo3,Qi Ping2,4 |
| (1.Party School of Liaoning Provincial Party Committee, Shenyang 110004, China;2.School of Economics, Jilin University, Changchun 130012, China;3. School of Economics, Shenyang University, Shenyang 110044, China;4.China State-owned Economy Research Center of Jilin University, Changchun 130012, China) |
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Abstract For a long time, China's manufacturing industry has been dependent on cost advantages to gain competitiveness. However due to the normalcy characterized with trade friction and disappearing population dividend, the cost advantages of China's manufacturing industry are difficult to sustain. At the same time, China is also faced with the situation that the core and key technologies in the upstream of the industrial chain are subject to foreign constraints. Therefore, it is necessary to make breakthroughs in innovation to maintain international competitiveness. At present, the digital economy based on digital technology has shown strong vitality and played an important role as an innovation engine under the continuous impact of the epidemic. The Chinese government is endeavoring to promote the high-end and intelligent development of manufacturing industry, create new growth engines such as new generation information technology and artificial intelligence, and improve the innovation efficiency of manufacturing industry. But in the process of rapid development of digital economy, the problem of unbalanced and inadequate development of digital industry within and between regions has become increasingly prominent. Against the backdrop of rapid development of the digital economy, further research is needed on the following questions: (1) what is the innovation efficiency of China's high-tech digital manufacturing industry? (2) is there a regional difference in the innovation efficiency of high-tech digital manufacturing industry?(3) is there a convergence mechanism for the innovation efficiency of high-tech digital manufacturing industry?#br#This study selects the data from 2009 to 2020 to measure and analyze innovation efficiency in 25 provinces. Drawing on existing research on innovation efficiency, the study divides the measurement of innovation efficiency into two stages: the first stage is the industrial research and development stage, and the second stage is the achievement transformation stage which is based on absorbing the achievements of the first stage of research and development. Thus it adopts the Super-SBM two-stage DEA model, Dagumn Gini coefficients and spatial convergence model to measure the innovation efficiency level of China's high-tech digital manufacturing industry from the perspective of value chain, and analyzes the dynamic characteristics of regional differences and spatial convergence of high-tech digital manufacturing industry.#br#The results show that (1) there is still a gap between the innovation efficiency of high-tech digital manufacturing industry in China and its optimal state, and the innovation efficiency in the east is significantly higher than that of other regions; (2) there are large differences in innovation efficiency between regions and within regions, and the sources of the differences in the two stages show different characteristics with significant changes in 2016; (3) the central R&D stage and the achievement transformation stage have had convergence characteristics since 2016, and the national level has significant spatial absolute and conditional convergence characteristics, while the eastern absolute convergence spatial characteristics have not passed the significance test. The findings are conducive to advancing an objective and comprehensive understanding of the current situation of innovation efficiency of China's digital manufacturing industry from the perspective of value chain, thus providing theoretical and empirical supports for how to strengthen the coordination and correlation between digital industry research and development and achievement transformation,upgrade the relevant industry chain, promote the development of the digital economy, improve the economic quality and avoid the regional digital gaps. #br#According to the above research conclusions, the marginal contributions of this paper are listed as follows: first, according to the classification of the digital economy industry by the National Bureau of Statistics, the two-stage innovation efficiency of high-tech digital manufacturing industry has been sorted and measured; second, the Dagumn Gini coefficient is used to measure the regional differences of innovation efficiency of high-tech digital manufacturing industry in China, and the spatial convergence characteristics of high-tech digital manufacturing industry are analyzed using the σ andβ convergence models.#br#
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Received: 01 November 2022
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