Advance in grey incidence analysis modelling

2011 ◽  
Author(s):  
Sifeng Liu ◽  
Hua Cai ◽  
Ying Cao ◽  
Yingjie Yang
Keyword(s):  
Grey Incidence Analysis ◽  
Incidence Analysis

Identifying key industry factors of remanufacturing industry using grey incidence analysis

2016 ◽  
Vol 6 (3) ◽  
pp. 398-414 ◽  
Author(s):  
Wenjie Liu ◽  
Jing Zhang ◽  
Chenfan Wu ◽  
Xiangyun Chang
Keyword(s):  
Grey System Theory ◽  
Grey System ◽  
Annual Sale ◽  
Content Type ◽  
Building Area ◽  
Industry Characteristic ◽  
Grey Incidence Analysis ◽  
Incidence Analysis ◽  
Practical Implications ◽  
Key Industry

Purpose The purpose of this paper is to identify most favorable (or quasi-preferred) industry characteristics of remanufacturing industry and most favorable (or quasi-preferred) industry factors which have an effect on these characteristics so as to improve these factors. Design/methodology/approach Grey system theory has prominent advantage of using few data and uncertainty information to analyze many factors. Therefore, it is more suited for system analysis than traditional statistical analysis methods like regression analysis, variance analysis and principal component analysis, which require massive data, certain probability distribution in the data and few variant factors. So in this paper, grey incidence analysis method, which is an important part of grey system theory, is used to identify industry characteristics and key industry factor of remanufacturing industry in China and then put forward appropriate industrial policies and countermeasures to improve these industry factors. Findings According to the results of this study, it reveals that there are no most favorable industry characteristics and no most favorable industry factors in remanufacturing industry of China. “Annual sale of remanufacturing industry” is identified as quasi-preferred industry characteristic, and “total number of employees with master degree or above in remanufacturing enterprise” is identified as the quasi-preferred industry factor. “Total building area of remanufacturing enterprise” is referred as the most unfavorable industry factors. Practical implications Judging from the findings of this study, four practical implications are summarized as follows: “annual sale of remanufacturing industry” should be given great importance because it is a quasi-preferred industry characteristic. “Total number of employees with master degree or above in remanufacturing enterprise” and “total number of research institution and university participated in remanufacturing” should be further strengthened by establishing an industry-university-research institute collaboration network, due to the fact that they are the top two quasi-preferred industry factors. “Total investment of remanufacturing industry” and “total annual R&D expenditures” have not played their due role in improving remanufacturing industry, so they should be moderately controlled so as to reduce waste of investment. “Total building area of remanufacturing enterprise” must be strictly controlled because of its little impact on remanufacturing industry. Originality/value In this research, grey incidence analysis is applied to identify key industry factors of remanufacturing industry for the first time. It helps in finding industry factors which are in urgent need of improvement and assists in making appropriate industrial policies and countermeasures to improve them by studying relationships between industry characteristic and industry factors.

An Evaluation Model of Enterprise Informatization Level Based on Grey Whitenization Weight Cluster Analysis

2011 ◽  
Vol 189-193 ◽  
pp. 823-829
Author(s):  
De Ling Yang ◽  
Wan Ming Chen
Keyword(s):  
Cluster Analysis ◽  
Index System ◽  
Evaluation Model ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Enterprise Informatization ◽  
Grey Incidence Analysis ◽  
Index Weight ◽  
Incidence Analysis

According to the existing insufficiency of researches of enterprise informatization level evaluation, building an evaluation model of enterprise informatization level based on grey whitenization weight cluster analysis. First, based on the existing research, build an evaluation index system of enterprise informatization level. Then, by using grey incidence analysis idea, put forward a method to determine index weight. And then, construt an evaluation model of enterprise informatization level based on grey whitenization weight cluster analysis. Finally, test the validity of the model through the application example.

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