| In the background of advocating the establishment of national innovation researching the innovation capacity of a city has a certain significance for the national leaderships to make the right decisions for cities’development. Innovation capabilities include many aspects, the innovation investment capability is the one aspect. It can fully reflect the city’s economic development as well as the leaders’ emphasis on the innovation ability. The purpose of the evaluation model is to understand the differences of each object on the indicators, it can provide a theoretical approach to help the makers to make rational scientific policy. This paper studies the evaluation model of independent innovation investment capacity of Fuzhou, Xiamen, Quanzhou, Sanming,Putian and Nanping these six Fujian cities in 2011. The investment capacity mainly includes the number of science and technology expenditure, expenditure on education, ordinary high school teachers and high school students. This can offer some suggestions for leaders of Fujian Province to make scientific policy for the development of these innovative capabilities in six different cities.The main purpose of this paper is threefold:(1) To explore the sorting situation about the innovation investment ability of these six cities in Fujian Province; (2)To further explore the availability of single evaluation models. These models are Entropy, Gray correlation method, Principal component analysis method and AHP; (3)To explore the more reasonable combination evaluation models of these six cities’innovation investment ability through the pre-post test of combination evaluation model.Firstly, establish the four single evaluation models of Entropy method, Gray correlation method, AHP and Principal component analysis method. Entropy model is obtained by using weighted summation formula to calculate the sample evaluation value, getting the evaluation of the six cities’values U=(0.6436,0.6957,0.7577,0.2737,0.2972,0.2221)T Gray correlation model is calculated by correlation coefficient, the correlation degree is B=(0.6761,0.6012,0.8139,0.3972,0.4199,0.383l)T; The Principal component analysis method model is to calculate the total score weighting coefficients to eigenvalue contribution rate, obtaine the comprehensive score F= 68.823F1+28.561F2,the comprehensive scores of each city respectively are F=(71.2601,-22.9713,113.4785,-58.3065,-35.4973,-67.9628)T;In this paper, the AHP model is constructed by expert judgement matrix, calculates a single sort value after the consistency test, and finally calculates the total order values w=(0.2524,0.3023,0.2733,0.0638,0.0663,0.0418)T.Secondly, explore the evaluation method for the integration of Pre-and post test, that can set the evaluation models, and establish the four combination models of the Mean value, Fuzzy Borda method, Minimum deviation method and Fitting method. The Mean value model is to transform the single model ranking value and then order the total values by The Fuzzy Borda method considers the score difference factors and calculates the fuzzy Borda fraction FB=(2.8000,4.1333,0.0667,9.3333,7.0000,11.6667)T. The Minimum deviation method model is to combine the Entropy method and AHP of subjective and objective optimization models, getting the evaluation value X=(0.4611,0.5171,0.5104,0.1714,0.1814,0.1308)T; Fitting model is to combine the Gray correlation analysis method and AHP, the evaluation value obtained by fitting is X=(0.6310,0.7437,0.6964,0.3848,0.3943,0.3664)T.Finally, base on the single and combined evaluation models, the conclusion is:the establishment of the subjective and objective combination models-- Minimum deviation model and Fitting model are more reasonable. The ranking of these six Fujian cities’ investment in innovation capability are as follows:Xiamen ranked first, Quanzhou second, Fuzhou third, the four five six were Putian, Sanming and Nanping. This is roughly consistent with the situation of the development of these cities in 2011.According to the different characteristics of the six cities’ economic development, corresponding suggestions are put forward:Xiamen should increase the investment of occupation technology education; Quanzhou is to increase the emerging industry technical inputs; Fuzhou must improve the input system in science and technology; Putian can rely on tourism to implement the leap forward development; Sanming can rely on food to increase science and technology investment; Nanping should make agriculture economy develop, that driven the technology and talents. Hope that these advices can provide some references for city development decision-making for the leaderships of the Fujian province.In this paper, according to the different models, it mainly by means of Matlab, SPSS, Lingo software to solve the models and has higher accuracy. |
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