Science Research Management ›› 2016, Vol. 37 ›› Issue (5): 122-131.

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A combination empowerment model based on variation coefficient weighted and its empirical study of S&T evaluation

Shi Baofeng1, Cheng Yanqiu2, Wang Jing1   

  1. 1. College of Economics & Management, Northwest A&F University, Yangling 712100, Shaanxi, China;
    2. School of Accounting, Dongbei University of Finance and Economics, Dalian 116025, Liaoning, China
  • Received:2014-06-02 Revised:2015-09-06 Online:2016-05-20 Published:2016-05-06

Abstract: The science and technology (S&T) evaluating index system of implicating the Scientific Development View Connotation is established, by using R cluster analysis to delete these indicators of reflecting repeated information, and using factor analysis to screen these indicators with the highest information content. On this basis, by combining the subjective G1 weight with the objective angle cosine weight utilizing the variation coefficient, the paper establishes a combination empowerment model based on variation coefficient weighted, and then carries out an empirical study of 14 typical provinces of China. The special and contributions of this paper lie on two aspects. Firstly, by combining the subjective G1 weight with the objective angle cosine weight utilizing the variation coefficient, the maximum objective function of combination weighting has been established. Then, the combination coefficient θ1 of the subjective G1 weight and the combination coefficient θ2 of the objective angle cosine weight can be calculated. At the same time, the empowering ideas that the bigger of the distribution variability between the subjective weighting and the objective weighting, the greater of the combination weighting, is reflected. Thus, the right time to make up the existing combination empowerment cannot effectively reflect the difference between the expert knowledge and the objective data, because the subjective weighting coefficient θ1 and the objective weighting coefficient θ2 is equal. Secondly, an empirical result show that the key factor of restricting Jiangxi and Guangxi S&T development is insufficient S&T input; the critical factor of constraining Sichuan S&T development is weak in science and technology's influence on the economic and social; the bottleneck element of restricting Heilongjiang, Shandong and Henan S&T development is insufficient S&T output.

Key words: combination empowerment, variation coefficient, S&T evaluation, G1 weighting, angle cosine weighting