Using the panel data of China’s 30 provinces between 2002 and 2014, this paper firstly employs super-efficiency DEA model to measure the R&D efficiency of each province. Secondly, selecting the R&D expenditure input intensity and government funds on R&D as indicators to quantify the regional R&D fairness, we establish Markov chain model and put China’s regional R&D fairness and efficiency into the united analysis framework where we compare the Matthew effect of them and build up implementing paths of their coordinated development. The results indicate that the Matthew effect of R&D fairness is more pronounced. Those districts which get heavy R&D funds constantly get ample funds, whereas most districts are invariably suffering from the embarrassment of lack of R&D expenditure. Therefore, more importance should be attached to the problem of R&D fairness. This paper concludes that the government should focus more on the district of low-input but high-efficiency and increase R&D expenditure on them which can not only weaken the Matthew effect of fairness but can also maintain the coordinated development of the regional R&D fairness and efficiency in China.
$author.xingMing_EN. A Comparison of Matthew Effect of China’s Regional R&D Fairness and Efficiency and the Implementing Path of their Coordinated Development——an Empirical Study Based on China’s Provincial Panel Data[J]. Studies in Science of Science, 2017, 35(12): 1832-1840.