Abstract
Based on panel data from 2008 to 2017, a BCC model and a DEA-Tobit model based on a three- stage DEA method are established to study the regional innovation capabilities and their influencing factors of 11 provinces and cities in the eastern coastal areas of China. The research finds that the innovation efficiency in the eastern coastal areas is still far from the frontier of innovation efficiency, and the low scale efficiency is the main factor restricting its development. In terms of influencing factors of innovation efficiency, improving technological level, optimizing market environment, and expanding enterprise scale can improve regional innovation efficiency, while the irrational expansion of the financial industry will hinder the development of innovation capabilities. Based on the research conclusions, policy suggestions such as actively exerting the effects of industrial agglomeration, deepening the reform of old industrial bases, and optimizing the innovation environment are put forward.
Highlights
General Secretary Xi Jinping pointed out in the report of the 19th National Congress of the Communist Party of China that China's economy has shifted from a high-speed growth stage to a high-quality development stage, and innovation is the key motivation for achieving highquality development
By summarizing the previous research results, we find that Chinese scholars have some research on regional innovation efficiency, but there is still room for improvement
The overall efficiency value of the eastern coastal areas increased from fluctuations from 2008 to 2017
Summary
General Secretary Xi Jinping pointed out in the report of the 19th National Congress of the Communist Party of China that China's economy has shifted from a high-speed growth stage to a high-quality development stage, and innovation is the key motivation for achieving highquality development. There are few studies on factors affecting regional innovation efficiency in China. This paper selects the three-stage DEA model, and combines the data of 11 provinces and cities in the eastern coast of China with 2008-2017 to estimate the regional innovation efficiency. Through research on relevant literature, it can be found that research funding and research staff's input have the greatest impact on regional innovation efficiency To this end, this article selects the stock of R & D funding internal expenditure after perpetual inventory method to measure the funding required for innovation. The main environmental factors affecting the efficiency of regional innovation include the level of the regional economy, the degree of openness to the outside world, the level of government support, and the scale of financial development. The basic data comes from websites such as China Statistical Yearbook of Science and Technology, China Statistical Yearbook, and National Bureau of Statistics
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