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.

scholarly journals Factors affecting the effectiveness of quality control circles in a hospital using a combination of fuzzy VIKOR and Grey Relational Analysis

2018 ◽  
Vol 27 (3) ◽  
pp. 180-186 ◽  
Author(s):  
Mohammadkarim Bahadori ◽  
Ehsan Teymourzadeh ◽  
Foad Faizy Bagejan ◽  
Ramin Ravangard ◽  
Mehdi Raadabadi ◽  
...  
Keyword(s):  
Quality Control ◽  
Grey Relational Analysis ◽  
Sampling Method ◽  
Reward System ◽  
Factors Affecting ◽  
Relational Analysis ◽  
Fuzzy Vikor ◽  
Use Of Resources ◽  
Grey Relational ◽  
Goals And Objectives

Background: One of the techniques used to achieve productivity, employees’ job satisfaction and higher quality goods and services, as well as to solve the problems by using a team, is the formation of quality control circles. Quality control circles enable managers to meet the organization’s and employees’ needs through making effective use of resources and facilities. On the other hand, the quality of services is always affected by uncertainty and ambiguous and implicit judgments, which make its measurement uncertain. Aim: The present study aimed to identify important factors affecting the effectiveness of quality control circles in a hospital, as well as rank them using a combination of fuzzy VIKOR and Grey Relational Analysis (GRA). Methodology: This was an applied, cross-sectional and descriptive–analytical study conducted in 2016. The study population consisted of five academic members and five experts in the field of nursing working in a hospital, who were selected using a purposive sampling method. Also, a sample of 107 nurses was selected through a simple random sampling method using their employee codes and the random-number table. The required data were collected using a researcher-made questionnaire which consisted of 12 factors. The validity of this questionnaire was confirmed through giving the opinions of experts and academic members who participated in the present study, as well as performing confirmatory factor analysis. Its reliability also was verified (α=0.796). The collected data were analyzed using SPSS 22.0 and LISREL 8.8, as well as VIKOR–GRA and IPA methods. Results: The results of ranking the factors affecting the effectiveness of quality control circles showed that the highest and lowest ranks were related to ‘Managers’ and supervisors’ support’ (Š = 6.80, [Formula: see text] = 0.36) and ‘Group leadership’ (Š = 2.63, [Formula: see text] = 0.98). Also, the highest hospital performance was for factors such as ‘Clear goals and objectives’ and ‘Group cohesiveness and homogeneity’, and the lowest for ‘Reward system’ and ‘Feedback system’, respectively. Conclusion: The results showed that although ‘Training the members’, ‘Using the right tools’ and ‘Reward system’ were factors that were of great importance, the organization’s performance for these factors was poor. Therefore, these factors should be paid more attention by the studied hospital managers and should be improved as soon as possible. Applying quality control circles in any organization is very helpful and provides opportunities for maximum use of employees’ creativity, initiative and skills in reaching their and their organization’s goals and objectives, and prepares favorable working conditions for the employees’ optimal performance through increasing the managers’ sense of responsibility and commitment.

Optimization of Reaming Process Parameters for Titanium Ti-6Al-4V Alloy Using Grey Relational Analysis

2016 ◽  
Author(s):  
Shakeel Ahmed L. ◽  
Pradeep Kumar M.
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Research Work ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Factors Affecting ◽  
Significant Control ◽  
Relational Analysis ◽  
Control Factors ◽  
Grey Relational

Reaming is one of the finishing processes that have been widely applied in manufacturing industries. Reaming of Titanium Ti-6Al-4V alloy material is an important and current research topic on manufacturing processes. Optimal process parameter setting is an important element in the machinability study of Titanium Ti-6Al-4V alloy. Optimization has most significant importance, particularly for reaming operations. This research work focuses on the multi-response optimization of reaming process parameters using the Taguchi and Grey relational technique to obtain minimum cutting temperature (T), thrust force (Ft), torque (Mt), surface roughness (Ra) and hole quality. The experiments were performed on Titanium Ti-6Al-4V alloy using uncoated carbide straight shank reamer under wet and cryogenic LN2 conditions. Eighteen experimental runs (L18) based on the Taguchi method of orthogonal arrays were performed to determine the best factor level condition. The environment, cutting speed and feed rate were selected as control factors. Grey relational analysis was used to determine the most significant control factors affecting the output parameters. Grey relational grade obtained from the grey relational analysis was used to solve the reaming process with the optimal levels of the multiple performance characteristics responses were established. The optimum results indicate that the reaming results have been improved in wet coolant than the cryogenic LN2 condition.

AN INTEGRATED APPROACH FOR SELECTING A VENDOR USING GREY RELATIONAL ANALYSIS

2006 ◽  
Vol 05 (02) ◽  
pp. 277-295 ◽  
Author(s):  
A. NOORUL HAQ ◽  
G. KANNAN
Keyword(s):  
Grey Relational Analysis ◽  
Integrated Approach ◽  
Vendor Selection ◽  
Chain Model ◽  
Factors Affecting ◽  
Relational Analysis ◽  
Selection Decisions ◽  
Proposed Model ◽  
Supply Chain Model ◽  
Grey Relational

This paper develops a new model for evaluating and selecting the vendor using an integrated approach of Grey Relational Analysis (GRA) along with an Analytical Hierarchy Process (AHP) in a Forward Supply Chain Model (FSCM). The paper aims to demonstrate how the model can help in solving such decisions in practice. It also examines the structure of the decision hierarchy, whether it can represent vendor selection decisions in reality and whether it covers all key factors affecting vendor selection choices. The effectiveness of the GRA model is illustrated with an Original Equipment Manufacturing (OEM) industry in southern part of India and the results of GRA were validated using the result obtained from AHP. The proposed model helps the industry to effectively select the vendor.

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.

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