| Sci-tech development of universities plays an important role in the national sci-tech development system, which provides essential support for the economic and social development in the long term. Under traditional education system, people focus more on the quantities of sci-tech projects applications in universities, but less on their efficiency and levels of achievements transformation. This thesis takes sci-tech input efficiency of universities as an entry point, and carries out combined static and dynamic analysis and calculation of sci-tech input efficiency of universities in 31 Chinese provinces through data envelopment (DEA-BCC) and Malmquist index. Meanwhile, multiple linear regressions are applied to find out the main influence factors on the efficiency. Finally, the suggestions are proposed for improving the sci-tech input efficiency of universities at the present stage.Methodology DEA-BCC static analysis on sci-tech input efficiency of universities in Chinese provinces shows that time evolution characteristics mainly take 2011 as watersheds; there is no obvious change with slight fluctuation before 2011; while with a trend of sharp rising from 2011 to 2014. In the aspect of spatial differentiation characteristics, the average value of sci-tech input efficiency of universities in east region is 0.377, which is higher than that of the rest of regions. After 2009, the gap of sci-tech input efficiency of universities is being extended. For example, in 2014, the sci-tech input efficiency of universities in eastern region is 0.226 (65.65%), higher than that in central regions, and is 0.268 (79.70%) higher than that in western regions.Malmquist index dynamic analysis on sci-tech input efficiency of universities in Chinese provinces suggests that the sci-tech input efficiency of Chinese universities is increasing with fluctuations in general. The average annual TFP is 1.097 with the growth rate 9.7%; the average annual progress index is 1.154 with the growth rate 15.4%. Meantime, the average annual technical efficiency changing index is 0.985, while the growth rate is-1.5%. The main force of TFP increase for sci-tech input in Chinese universities is technical progress; while the contribution of technical efficiency changing is negative. As for TFP distributions of sci-tech input of universities in Chinese provinces, the difference of TFP is not distinct. The number of TFP index in the range of 1-1.2 is 22 among 31 provinces, accounting for 70.97%; the number of TFP index over 1.2 is 4, accounting for 12.90%; and the number of TFP index less than 1.0 is 5, accounting for 16.13%. The gap between eastern and western regions is the key point.Regression analysis on the factors in influencing sci-tech input efficiency of universities in Chinese provinces shows that there is a positive correlation between the number of authorized patents and published papers, the proportion of basic research expenditures (expenditures for the year), the ratio of senior professional titles in R&D staff and output efficiency; while a negative correlation between the number of full-time R&D staff and output efficiency.The main contents of the thesis show as follow:Chapter 1 briefly elaborates the writing background, significance, methodologies and basic writing thoughts of the paper; sources of data are also explained.Chapter 2 presents studies on sci-tech input and output efficiency of Chinese universities in two aspects from both home and abroad.Chapter 3 analyzes and judges the trend of sci-tech input and output of universities in 31 Chinese provinces, which can be divided into two parts. One is carrying out integral analysis and trend judgment from the aspects of manpower and expenditure for the sci-tech input; the other is from the aspects of the number of authorized patents, published papers and actual income of technology transfer of each year.Chapter 4 carries out empirical analysis on the sci-tech input efficiency of universities in Chinese provinces, including:1) selection of efficiency measuring model; 2) establishment of evaluating index system for sci-tech input efficiency of Chinese provincial universities; 3) analysis on time evolution and spatial differentiation of sci-tech input efficiency of universities in Chinese provinces based on DEA-BCC model; 4) dynamic analysis on sci-tech input efficiency of universities based on Malmquist index, mainly from the angle of promotional forces and regional differences.Chapter 5finds out the significant factors in influencing sci-tech input efficiency of universities in Chinese provinces via multiple linear regressions. The main analyzing factors are manpower, material resources, financial resources and achievements of sci-tech input of universities in order to find out the key influence factors and degrees.Summary of the paper is drawn in Chapter 6, proposing suggestions on promoting the sci-tech input efficiency of Chinese universities by way of system innovating, management progressing, evaluation system improving. |
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