CHEMICAL ENGINEERING TRANSACTIONS VOL. 51, 2016 A publication of The Italian Association of Chemical Engineering Online at www.aidic.it/cet Guest Editors: Tichun Wang, Hongyang Zhang, Lei Tian Copyright © 2016, AIDIC Servizi S.r.l., ISBN 978-88-95608-43-3; ISSN 2283-9216 Based on Hierarchy Analysis Model of the New Rural Cooperative System Development Related Research Hua Wanga, Xuhui Yin*b a College of Humanities and Social Development, Northwest A&F University, Yangling 712100, Shaanxi, China b School of Marxism, Northwest A&F University, Yangling 712100, Shaanxi, China 31415234882@qq.com The new rural cooperative system development has become a focus in the study of today's problem, in this paper, by applying the analytic hierarchy process (ahp) model for the new rural cooperative system development problem to do the research, the choice of the weight of each indicator gives numerical, after that will develop the new rural cooperative system model is applied in the 14 parts of China on the issue of development of the new rural cooperative system. Finally, it is concluded that the ranking of various areas, including Changsha somewhere in various indicators ranked first, prove that the new type of rural cooperative system of the region is good and consistent with the actual development, illustrates the rationality and validity of the model. 1. Introduction Cooperative has already become a trend in current social development, as a kind of market economy system, it drives rural economy to steady move forward, due to the aspect emergency in China is later than foreign countries, it has many imbalanced phenomenon, and so research on rural cooperatives has important significances in current new rural development (He and Lu, 2009). Xue Ping in comparison of domestic and foreign rural cooperatives theories development, found Chinese rural cooperatives correlation theories shortcomings by comparing each country legislation and academic aspects, and through discussion on comparison of China and foreign countries, she put forward suggestions to perfect China’s rural cooperatives countermeasures, verified feasibility and effectiveness of developing new pattern rural cooperatives (Zhang et al., 2013). Just on the basis of above researches, the paper carries on further analysis and researches on new pattern rural cooperatives development problems, makes quantization on them by applying questionnaire survey, analytic hierarchy process and other methods, the result is reasonable and effective (Huang and Yang, 2011). 2. Indicators selection After entering into 21st century, China joined into WTO organization, its economy gradually fused into world economy entity, China’s agricultural products and others due to family decentralized operation, it caused low competitiveness, low productivity as well as other drawbacks increasing, in the background of one place market economy gradually fusing into rural small-peasant economy, peasants started to establish various of producers’ cooperatives (Chen and Wu, 2009), from which it mainly includes: economic complex, professional association, professional cooperatives, community cooperatives and so on, then, with economic development (Zheng, 2015), China established new pattern rural cooperatives, but from which some aspects were urgently to be improved, main aspects were as following (Zhang et al., 2015): (1) Government roles in new rural cooperatives development were relative fuzzy; (2) New rural cooperatives continuously development weakness; (3) New rural cooperatives lacked of normalized internal running mechanism; (4) New rural cooperatives professional extent was not good enough; DOI: 10.3303/CET1651145 Please cite this article as: Wang H., Yin X.H., 2016, Based on hierarchy analysis model of the new rural cooperative system development related research, Chemical Engineering Transactions, 51, 865-870 DOI:10.3303/CET1651145 865 (5) New rural cooperatives scales were small, proportions were little; (6) New rural cooperatives cover area was small, cooperation extent was single To solve above problems, the paper studies system development problems of them, selects correlation indicators from “New rural cooperatives” and other articles, analyzes obtained data by questionnaire survey, mathematical statistics and other methods (Chen, 2013), finally it gets each indicator table as following Table 1: Table 1: New rural cooperatives system development problem system table First grade indicator Second grade indicator Third grade indicator U1 Insurance system T1 System requirements T11 City one location scale T12 Techniques T13 Constitutional order T14 Product price changes T15 Factor price changes T16 Marketing channel T2 New rural social insurance system T21 Peasants aged relief law T22 Aged and disabled social insurance law T23 Work injury insurance law T24 Sickness insurance law U2 Legal safeguard T3 System conditions T31 Interaction between supply and demand T32 System innovation T33 Balance between supply and demand T4 System supplies T41 Constitutional order T42 Anticipated system cost T43 System designing cost T5 System accumulation T51 Upper level decision net profit T52 Current system arrangement T53 Knowledge accumulation T6 Cooperative medical care system T61 Financial aid T62 Social relief and aid T63 Typical system fostering T7 Vulnerable groups security system T71 Legal aid system T72 Minimum subsistence guarantee system T73 Execution of rescuing measures 3. Model establishments AHP features are layering complicated problems, making clear about primary and secondary, possessing stronger logicality and hierarchical structure, the algorithm mainly is calculating indicators’ weights. It is applicable to comprehensive assessment system, is a powerful mathematical method that converts problems into quantitative research. Nowadays analytic hierarchy process has already widely used in each field to solve practical problems (Cai and Cao, 2015). New pattern rural cooperatives system development problem involves multiple reference indicators; the decision problem is suitable to analytic hierarchy process. Analytic hierarchy process respectively reflect each factor interactive relationship both in horizontal and vertical directions, due to decision-maker weights on different factors are not certainly the same, so it establishes hierarchical structure model to compare mutual importance, therefore it needs to construct judgment comparison matrix. In formula, bij the two compared importance uses quantized value to express, it uses 1-9 number to describe, and number representative meaning is as following Table 2 show: Table 2: 1-9 scale meaning Scale Meaning 1 Indicates two factors have equal importance by comparing 3 Indicates the former is slightly more important than the later by comparing two factors 5 Indicates the former is more important than the later by comparing two factors 7 Indicates the former is relatively more important than the later by comparing two factors 9 Indicates the former is extremely more important than the later by comparing two factors Even number Represents importance is between two odd numbers Reciprocal Represents factors positive and negative comparison order 866 3.1 Weight vector and maximum features calculation According to first grade indicators judgment matrix vectors, carry on normalization processing with them, solve the sum by line and then make normalization, it can get weight vectors. According to feature values and feature vectors relationships, it can solve feature values. 3.2 Consistency test To matrix u=(bij)n*n, if matrix element meets bijbjk=bk, then matrix is consistent matrix. Among them, bij>0, bij=1/bii. In order to use it to calculate factor weight, it requires that matrix inconsistency only under acceptable conditions. When problems are relative complicated, we cannot take all factors into account, which causes paired comparison construct judgment matrix instant, judgment matrix cannot arrive at ideal state consistency. Judgment matrix consistency indicator CI, and judgment matrix consistency ratio CR, its computational method is as following formula show: CI=(λmax-n)/(n-1) Among them, n represent order number of judgment matrix that is also the number of compared factors: RI CI CR = Among them, RI represents Random Consistency Index value. When CR≥0.1, it is thought that judgment matrix occurs inconsistency that needs to make adjustment on judgment matrix again. When CR<0.1, judgment matrix inconsistency is within acceptable range. Next step is doing combination consistency testing. Assume that in one layer, m pieces of factors weight calculation result is αm, corresponding consistency indicator value respectively is CIm, combination consistency test consistency ratio is:   = == m j jj m j jj RI CI CR 1 1 α α By calculating, combination consistency ratio calculated value is: CR<0.1 So hierarchical total arrangement’s consistency testing meets consistency requirement. 3.3 Weight calculation arrangement If in one layer, m pieces of factors weight calculation result is αm, corresponding consistency indicator value respectively is CIm, in next layer n pieces of factors to A layer calculation weight is βnm, then in T layer factors total arrangement weight is:  = = m j ijiiw 1 βα By above formula calculating, it gets each indicator weight in total target. 3.4 Model application By using yaah0.53 software, the paper scores new pattern rural cooperatives system development problem involved each indicator, firstly it needs to define judgment matrix, calculate new pattern rural cooperatives system development problems evaluation, specific process is as following Table 3-13 shows: Table 3: New pattern rural cooperatives system development problem second grade judgment matrix and weights A U1 U5 wi U1 1 1/5 0.5556 U5 5 1 0.6666 Table 4: New pattern rural cooperatives system development problem U1 fourth grade judgment matrix and weights U1 T1 T2 T3 T4 wi T1 1 1/5 5 5 0.5511 T2 5 1 5 5 0.3900 T3 1/5 1/5 1 5 0.1654 T4 1/5 1/5 1/5 1 0.1143 Note: Weight on total target: 0.5555; Judgment matrix consistency proportion: 0.0343; 867 Table 5: New pattern rural cooperatives system development problem U2 third grade judgment matrix and weights U2 T5 T6 T7 wi T5 1 1 1 0.5555 T6 1 1 1 0.5555 T7 1 1 1 0.5555 Table 6: New pattern rural cooperatives system development problem T1 sixth grade judgment matrix and weights T1 T11 T15 T15 T13 T14 T16 wi T11 1 4 1/5 1 1/5 1/5 0.1142 T15 1/4 1 1/8 1 1/6 1/4 0.0308 T15 5 8 1 3 1 5 0.5199 T13 1 1 1/3 1 1/3 1/5 0.0736 T14 5 6 1 3 1 1 0.5459 T16 5 4 1/5 5 1 1 0.1945 Table 7: New pattern rural cooperatives system development problem T2 fourth grade judgment matrix and weights T2 T21 T22 T23 T24 wi T21 1 1/4 1 1/5 0.1055 T22 4 1 5 1 0.5974 T23 1 1/5 1 1/4 0.1057 T24 5 1 4 1 0.5972 Table 8: New pattern rural cooperatives system development problem T3 fourth grade judgment matrix and weights T3 T31 T32 T33 wi T31 1 5 5 0.4579 T32 1/5 1 1/5 0.1595 T33 1/5 5 1 0.5554 Table 9: New pattern rural cooperatives system development problem T4 third grade judgment matrix and weights T4 T41 T42 T43 wi T41 1 5 5 0.4955 T42 1/5 1 5 0.5396 T43 1/5 1/5 1 0.1471 Table 10: New pattern rural cooperatives system development problem T4 third grade judgment matrix and weights T5 T51 T52 T53 wi T51 1 5 5 0.410 T52 1/5 1 1 0.5300 T53 1/5 1 1 0.5400 Table 11: New pattern rural cooperatives system development problem T6 third grade judgment matrix and weights T6 T61 T62 T63 wi T61 1 5 5 0.3952 T62 1/5 1 1/5 0.1949 T63 1/5 5 1 0.5108 868 Table 12: New pattern rural cooperatives system development problem T7 third grade judgment matrix and weights T7 T71 T72 T73 wi T71 1 5 1/5 0.5971 T72 1/5 1 1/5 0.1652 T73 5 5 1 0.4596 Table 13: New pattern rural cooperatives system development problem final weights Alternative offer Weight Alternative offer Weight Alternative offer Weight T11 0.0088 T53 0.0639 T45 0.0445 T15 0.0051 T51 0.0586 T61 0.1096 T15 0.0535 T55 0.0076 T65 0.0352 T13 0.0048 T55 0.0182 T65 0.0694 T14 0.0198 T31 0.0559 T71 0.0660 T16 0.0141 T35 0.0097 T75 0.0561 T51 0.0168 T35 0.0065 T75 0.1190 T55 0.0638 T41 0.1112 T55 0.0167 T45 0.0447 4. Application examples In order to clearly present the model effectiveness, the paper researches on China’s 14 regions new pattern rural cooperatives system development problems, and applies above process into the examples, gets each indicator second grade scores, arranges them, as following Table 14: Table 14: Fourteen regions new pattern rural cooperatives development scores and ranking C1 C2 C3 C4 C5 C6 C7 S core R anking S core R anking S core R anking S core R anking S core R anking S core R anking S core R anking Changsha city 7.72 1 16.34 1 5.48 1 3.85 1 22.22 1 22.24 1 22.22 2 Hengyang city 6.01 3 12.05 5 5.38 3 2.91 3 9.51 12 18.54 8 14.15 9 Xiangtan city 6.46 2 12．87 3 4.36 6 2.94 2 16.71 2 22.24 1 22.75 1 Zhuzhou city 5.29 6 10.42 9 3.67 12 2.73 4 14.48 3 16.67 13 16.94 6 Changde city 4.60 13 9.01 13 4.01 8 2.05 10 11.35 9 17.35 11 15.54 7 Yueyang city 5.69 5 11.18 7 5.44 2 2.53 5 13.64 4 19.77 5 18.05 3 Shaoyang city 5.77 4 10.04 10 4.36 6 2.44 7 11.52 8 18.54 8 17.98 4 Zhangjiajie 5.12 10 11.87 6 3.13 14 1.88 12 8.92 13 21.13 3 15.45 8 Yongzhou city 5.20 8 13.13 2 4.89 4 2.47 6 11.58 7 19.21 6 13.72 11 Chenzhou city 5.27 7 9.08 12 4.77 5 2.35 8 9.23 11 14.89 14 13.88 10 Yiyang city 5.12 9 9.86 11 4.06 9 2.28 9 11.79 6 18.19 10 17.26 5 Huaihua city 4.65 12 10．55 8 3.99 10 1.87 13 8.80 14 19.06 7 12.24 12 Xiangxi Autonomous Prefecture 5.07 11 12.72 4 3.16 13 1.93 11 12.08 5 21.35 4 11.12 13 Loudi city 4.29 14 8.80 14 3.83 11 11.71 14 10.59 10 17.23 12 9.08 14 Average value 5.45 / 11.27 / 4.33 / 2.42 / 12.30 / 19.03 / 15.75 / Standard deviation 0.87 / 2.07 / 0.78 / 0.57 / 3.62 / 2.16 / 3.85 / Apply Excel software to process with above calculation result, and apply formula ISA= ii SW (from which S represents each factor standard value, W represents corresponding weight) therefore we can get each indicator total scores, and arrange them that result is as following Table 15 shows: 869 Table 15: Each region comprehensive ranking U1 U2 U3 Score Ranking Score Ranking Score Ranking Changsha city 33.3 1 66.6 1 100.0 1 Hengyang city 26.36 3 42. 11 68.7 7 Xiangtan city 26.5 2 61.7 2 88.3 2 Zhuzhou city 21.8 9 48. 4 69.9 6 Changde city 19.7 13 44. 10 62. 11 Yueyang city 24.8 5 51.0 3 75.9 3 Shaoyang city 22.6 7 48.0 5 70.6 4 Zhangjiajie 22.0 8 45.5 7 67.5 9 Yongzhou city 25.70 4 44.5 9 70.2 5 Chenzhou city 21.4 10 38.0 13 59.4 13 Yiyang city 21.3 11 47.2 6 68.5 8 Huaihua city 21.0 12 40.1 12 61.1 12 Xiangxi Autonomous Prefecture 22.8 6 44.5 8 67.42 10 Loudi city 18.6 14 36.9 14 55.5 14 Average value 23.4 / 47.0 / 70.4 / Standard deviation 3.7 / 8.31 / 11.5 / 5. Conclusion The paper researches new pattern rural cooperatives system development problem model by applying analytic hierarchy process method, and assigns values on selected each indicator weight, after that applies new pattern rural cooperatives system development problem model into practical problem, makes statistics of China’s 14 regions’ new pattern rural cooperatives system development problem’s second grade indicators, first grade indicators scores and final scores, gets each region ranking, from which Changsha city one place respectively ranks first in each indicator, it proves the region new pattern rural cooperatives system development is good, it is just consistent to practices. Acknowledgements Northwest agriculture and Forestry University of science and technology, humanities and social science project: the rural basic education resource allocation fairness problem research (item number 2015 rwyb15). 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