scholarly journals Analysis of Rural Talent Scale in Hebei Province Based on Fractional GM (1,1) and the Grey Relational Analysis Model

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yibo Li ◽  
Wenbin Bi ◽  
Kuo Xiao ◽  
Huan Li ◽  
Shi Yin ◽  
...  
Keyword(s):  
Grey Relational Analysis ◽  
Hebei Province ◽  
Analysis Model ◽  
Relational Analysis ◽  
Rural Income ◽  
Rural Revitalization ◽  
Urban Rural ◽  
Service Oriented ◽  
Countermeasures And Suggestions ◽  
Grey Relational

Talents are the key of rural revitalization. Under the background of Beijing-Tianjin-Hebei Coordinated Development, Hebei Province has always put talent revitalization at the core of rural revitalization. In order to promote the process of rural revitalization in Hebei Province, it is very important to understand the scale of rural talents. Firstly, the GM (1,1) model was used to predict the scale of rural talents in Hebei Province from 2020 to 2025. The prediction results showed that, in the rural development of Hebei Province in the next few years, the scale of production-oriented talents would gradually decline, while the scale of service-oriented, business-oriented, management-oriented, and skilled talents would show varying degrees of growth. Secondly, the grey relational analysis was used to analyze the importance of different factors for rural talents. Through the grey relational analysis, it was found that the infrastructure had the greatest impact on production-oriented talents, the agricultural industrialization operating rate had the strongest impact on service-oriented talents, and the urban-rural income level had the greatest impact on business-oriented talents, management-oriented talents, and skilled talents. Finally, according to the results of the GM (1,1) model and grey relational analysis, aiming at different types of rural talents, this paper puts forward countermeasures and suggestions from the aspects of strengthening rural infrastructure construction, improving rural medical and health conditions and improving income distribution pattern.

Negative grey relational model and measurement of the reverse incentive effect of fields medal

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sifeng Liu
Keyword(s):  
Grey Relational Analysis ◽  
Research Output ◽  
Analysis Model ◽  
Content Type ◽  
Relational Analysis ◽  
Fields Medal ◽  
Definition Of ◽  
Grey Relational ◽  
Analysis Models ◽  
The Relationship

PurposeThe purpose of this paper is to construct some negative grey relational analysis models to measure the relationship between reverse sequences.Design/methodology/approachThe definition of reverse sequence has been given at first based on analysis of relative position and change trend of sequences. Then, several different negative grey relational analysis models, such as the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model have been put forward based on the corresponding common grey relational analysis models. The properties of the new models have been studied.FindingsThe negative grey relational analysis models proposed in this paper can solve the problem of relationship measurement of reverse sequences effectively. All the new negative grey relational degree satisfying the requirements of normalization and reversibility.Practical implicationsThe proposed negative grey relational analysis models can be used to measure the relationship between reverse sequences. As a living example, the reverse incentive effect of winning Fields Medal on the research output of winners is measured based on the research output data of the medalists and the contenders using the proposed negative grey relational analysis model.Originality/valueThe definition of reverse sequence and the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model are first proposed in this paper.

Appliance on Evaluation of Type Selection for Agricultural Machinery Based on Grey Relational Analysis Method

2011 ◽  
Vol 55-57 ◽  
pp. 988-991 ◽  
Author(s):  
Yan Xie ◽  
Mu Li
Keyword(s):  
Grey Relational Analysis ◽  
Analysis Method ◽  
Agricultural Machinery ◽  
Analysis Model ◽  
Relational Analysis ◽  
Type Selection ◽  
The Index System ◽  
Selection For ◽  
Grey Relational ◽  
Optimal Type

The type selection for agricultural machinery generally depends on the selector’s experiences at the present time. It exist some subjectivity and one-sidedness unavoidably. On the basis of the characteristics of complexity and the uncertainty of optimal selection for agricultural machinery, grey relational analysis model in agricultural machinery multi-type selection application has been put forward in this paper. The index system of influencing agricultural machinery type selection is determined. Application model and procedures of the grey relational analysis method are introduced. According to the degree how close it is with the ideal dot, the optimal type is easy to be selected out. Through the optimization analysis type selection for the agricultural transporter, it is proved that the optimal type selection for agricultural machinery based on grey relational analysis has the strong recognition judgment ability. It is convenient, quantitative, and strict. It provided a new method and a possible new way for evaluation of agricultural machinery type selecting．

scholarly journals External Financing Efficiency of Rural Revitalization Listed Companies in China—Based on Two-Stage DEA and Grey Relational Analysis

2019 ◽  
Vol 11 (16) ◽  
pp. 4413
Author(s):  
Xianhua Tan ◽  
Sanggyun Na ◽  
Lei Guo ◽  
Jing Chen ◽  
Zhihua Ruan
Keyword(s):  
Capital Structure ◽  
Grey Relational Analysis ◽  
Rural Areas ◽  
Listed Companies ◽  
Governance Structure ◽  
Two Stage ◽  
Factors Affecting ◽  
Relational Analysis ◽  
Rural Revitalization ◽  
Grey Relational

Rural revitalization is an important strategy to promote sustainable development of rural areas in China. Rural revitalization listed companies play an important role in implementing the rural revitalization strategy and developing the agricultural industry. However, the financing problem has always been a bottleneck problem with Chinese listed companies. This study used a two-stage DEA (data envelopment analysis) method to evaluate the funds raising efficiency, funds using efficiency, and overall financing efficiency of 34 rural revitalization listed companies in 2018. The results show that the financing efficiencies of 34 sample companies were low, only six companies have overall efficient financing, and there was much room for improvement. Financing efficiency varied greatly depending on the nature of the company, the industry, and the listing board. The efficiency of funds using of state-owned enterprises was much lower than that of private companies. The average efficiency value of agricultural company funds raising was lower than that of manufacturing. The efficiency of small and middle-size enterprises (SMEs) was lower than that of main board companies, but the growth enterprise market (GEM) companies achieved higher efficiency in the funds using. Further, by using the grey relational analysis (GRA) method, we found that the key factors affecting the financing efficiency of sample companies included capital structure, debt-paying ability, governance structure, company age, and operating ability. To improve financing efficiency, the companies should not only optimize their capital structure and governance structure but also improve their management and innovation capabilities. At the same time, the state also needs to give different policies support according to the characteristics of the companies.

Sign in / Sign up

Export Citation Format

Share Document