Applying Grey Relational Analysis and Grey Decision-Making to evaluate the relationship between company attributes and its financial performance—A case study of venture capital enterprises in Taiwan

2007 ◽  
Vol 43 (3) ◽  
pp. 842-852 ◽  
Author(s):  
Chaang-Yung Kung ◽  
Kun-Li Wen
Keyword(s):  
Decision Making ◽  
Venture Capital ◽  
Financial Performance ◽  
Grey Relational Analysis ◽  
Relational Analysis ◽  
Grey Relational ◽  
The Relationship

Decision Making on Engineering Materials Based on Relative Grey Relation Analysis

2013 ◽  
Vol 753-755 ◽  
pp. 1620-1624
Author(s):  
Dong Jing Wang ◽  
An Hua Peng
Keyword(s):  
Decision Making ◽  
Grey Relational Analysis ◽  
Maximum Deviation ◽  
Grey Relation Analysis ◽  
Relational Analysis ◽  
Relation Analysis ◽  
Engineering Materials ◽  
Grey Relational ◽  
The Relationship ◽  
Grey Relation

The quality and cost of a product rely heavily on selecting suitable engineering materials, and therefore the ability to select the most appropriate material for a given application is the fundamental challenges faced by the design engineer. The general grey relational analysis (GRA) has three weaknesses: (1) weight determination depends only on expert judgments; (2) the qualitative indexes are only simply quantified with exact number; and (3) the general GRA only takes into account the relationship between the imaginarily best material and the candidate materials. The GRA is extended to RGRA, weights are determined by combining subjective and objective weights based on maximum deviation, and the qualitative indexes are fuzzily quantified through trapezoidal fuzzy number (TFN). The illustrative example shows that the presented method enables decision making results to be more reasonable and trustworthy.

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.

Grey relational analysis between Turkey’s macroeconomic indicators and domestic savings

2017 ◽  
Vol 7 (1) ◽  
pp. 45-59 ◽  
Author(s):  
Engin Duran ◽  
Burcu Uzgur Duran ◽  
Diyar Akay ◽  
Fatih Emre Boran
Keyword(s):  
Grey Relational Analysis ◽  
Data Set ◽  
Content Type ◽  
Relational Analysis ◽  
Domestic Savings ◽  
Macroeconomic Indicators ◽  
Private Savings ◽  
Grey Relational ◽  
High Degree ◽  
The Relationship

Purpose It is of great importance for economy policy makers to comprehend the relationship between macroeconomic indicators and domestic savings, and to find out which indicator is more determinative on the dynamics of domestic savings. The purpose of this paper is to analyze the degree of relationship between Turkey’s domestic savings and selected macroeconomic indicators. Design/methodology/approach To examine the relationship, grey relational analysis (GRA) is applied together with the entropy method to determine the weight of the indicators according to the information level they provide. The analysis covers the data of the period from 1990 to 2014. In practice, however, the data set is used by dividing into two separate periods including before and after the 2001 crisis. Findings The results indicate that the unemployment rate and the gross domestic product (GDP) per capita growth stand out with a relatively high degree of relationship for the period before 2001. When examining the post-2001 period, current balance ratio and GDP growth are ascertained as indicators which have a high degree of relationship with domestic savings. Practical implications These indicators have different aspects affecting both public and private savings. Therefore, it may be beneficial to concentrate on these indicators when designing a policy in order to increase the domestic saving rate. Originality/value There are many econometric models used for investigating Turkey’s macroeconomic indicators and domestic savings causality. But before now, any study which investigates relationship between macroeconomic indicators and domestic savings by GRA could not be encountered. Using one of the newest developed theories (the grey systems theory) for this subject is the significance of this research.

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