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author:

Yang, Long-Hao (Yang, Long-Hao.) [1] | Ye, Fei-Fei (Ye, Fei-Fei.) [2] | Wang, Ying-Ming (Wang, Ying-Ming.) [3] | Huang, Yan (Huang, Yan.) [4] | Hu, Haibo (Hu, Haibo.) [5]

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EI

Abstract:

Performance evaluation is one of the most important standards to measure the competitiveness and productivity of enterprises. Although existing studies could obtain the specific values of enterprises performance based on historical data, they usually failed to effectively evaluate enterprises performance in the consideration of different indicators. Meanwhile, as the characteristics of existing performance evaluation models are uneven, how to choose a reasonable data envelopment analysis (DEA) model for enterprises performance evaluation must be considered. Therefore, a new ensemble model on the basis of homogeneous, heterogeneous, and hybrid efficiency evaluation together with the evidential reasoning (ER) approach is proposed in this study for enterprises performance evaluation, so called the ER-based ensemble model. The ER-based ensemble model can overcome the inconsistency results caused by the application of different indicators and different DEA models. In case study, 40 state-own holding enterprises in China are selected and all these enterprises are evaluated and ranked using the integrated efficiency obtained from the ER-based ensemble model. Comparative analysis demonstrates that the ER-based model is better than some traditional efficiency evaluation models in enterprises performance evaluation and performance ranking. © 2023 - IOS Press. All rights reserved.

Keyword:

Competition Data envelopment analysis Efficiency

Community:

  • [ 1 ] [Yang, Long-Hao]Decision Sciences Institute, Fuzhou University, Fuzhou, China
  • [ 2 ] [Ye, Fei-Fei]School of Cultural Tourism and Public Administration, Fujian Normal University, Fuzhou, China
  • [ 3 ] [Wang, Ying-Ming]Decision Sciences Institute, Fuzhou University, Fuzhou, China
  • [ 4 ] [Huang, Yan]College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou, China
  • [ 5 ] [Hu, Haibo]Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hong Kong

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Source :

Journal of Intelligent and Fuzzy Systems

ISSN: 1064-1246

Year: 2023

Issue: 2

Volume: 45

Page: 2477-2495

1 . 7

JCR@2023

1 . 7 0 0

JCR@2023

ESI HC Threshold:32

JCR Journal Grade:3

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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