Generalized grey information entropy weight TOPSIS model for financial performance evaluation considering differentiation
ISSN: 0368-492X
Article publication date: 2 August 2022
Issue publication date: 9 November 2023
Abstract
Purpose
Financial performance has been paid attention at an unprecedented level, which can be confirmed as a fact that the quantitative expansion of financial performance evaluation work. The purpose of this study is to propose a more appropriate model for financial performance evaluation under the unbalanced development.
Design/methodology/approach
This paper introduces the differentiation criteria to eliminate the deviation caused by the same principle for multiple performance evaluation objects whose development are unbalanced; Then the generalized grey number is adopted to describe the value of performance evaluation index; and the information entropy weight is used to obtain the index weight to reduce the artificial judgment error; Finally, the generalized grey information entropy weight TOPSIS evaluation model is constructed.
Findings
Empirical research shows that in the new evaluation model, the differentiated possibility function effectively eliminates the deviation caused by the same principle, the application of information entropy weight reduces the human judgment error, and the value of generalized grey number further enhances the closeness of the results. Moreover, it is also found that in different scenarios, an adaptive performance evaluation model should be selected to match scientifically reasonable results.
Originality/value
The proposed model offers a solution for financial performance evaluation considering unbalanced development among cities. It can be realized by determining the differentiation possibility function matrix, and then the information entropy weight TOPSIS evaluation model can be constructed. This model reflects the actual situation, improves the performance evaluation accuracy, and can be used under similar conditions.
Keywords
Acknowledgements
This work was supported by a projects of the National Natural Science Foundation of China (72071111, 71801127, 71671091).
Citation
Zhang, S., Liu, S., Fang, Z., Zhang, Q. and Zhang, J. (2023), "Generalized grey information entropy weight TOPSIS model for financial performance evaluation considering differentiation", Kybernetes, Vol. 52 No. 11, pp. 5412-5426. https://doi.org/10.1108/K-03-2022-0418
Publisher
:Emerald Publishing Limited
Copyright © 2022, Emerald Publishing Limited