Currently, for the evaluation of enterprise credit, many specific values of indexes are difficult to obtain, so decision makers tend to give a form of uncertain linguistic variable. To solve this kind of problem, the purpose of this paper is to introduce an uncertain pure linguistic approach on evaluation of enterprise integrity based on grey information.
Initial uncertain linguistic variables given by experts are transferred into interval grey numbers, and their greyness of degree is computed. Then, the greyness of degree is applied to adjust the weights of experts. Moreover, the core of each interval grey number is calculated, and through giving the positive ideal point and negative ideal point, which are binary numbers, the comprehensive grey relational grade between the linguistic number and the two points is calculated, respectively, as well to get the ranking result of projects by considering both core and greyness of degree.
The model is applied to a case, and the result verifies the validity and practicability of the model which reveals high effectiveness.
This model provides a new feasible method in a growing number of fuzzy evaluation schemes in the fields of enterprise integrity and contributes to getting better and more accurate results.
In this paper, the greyness of degree is introduced to the model to adjust the experts’ weights, and it reflects the thought of “making full use of the information” in grey system theory and further enriches the system of grey decision-making theory as well as expanding its application scope.
This work was supported by the National Natural Science Foundation of China (No. 71171112, 71502073), the Key Project of National Social Science Foundation of China (No. 14AZD049), the Research Funds for the General Virtual Economy (GX20131017(M)), the Scientific Innovation Research of College Graduate in Jiangsu Province (No. KYZZ15_0094).
Ma, Z. and Zhu, J. (2016), "An uncertain pure linguistic approach on evaluation of enterprise integrity based on grey information", Grey Systems: Theory and Application, Vol. 6 No. 3, pp. 353-364. https://doi.org/10.1108/GS-09-2015-0050Download as .RIS
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