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A new cross-efficiency aggregation in data envelopment analysis: considering fairness mentality and group consensus

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Abstract

Cross-efficiency evaluation (CEE) is an effective tool for ranking decision-making units (DMUs). The traditional data envelopment analysis (DEA) model employs self-evaluation to measure the performance of DMUs. CEE, as an extension of the DEA, includes self-evaluation and peer-evaluation, assessing the overall performance of each DMU through its own weights and the weights of all DMUs. The current CEE, however, aggregates self-evaluation and peer-evaluation efficiencies mostly via the arithmetic average, which underestimates the importance of self-evaluation and ignores the subjective preferences of decision-makers as well. To address this deficiency, considering the fairness mentality of decision-makers, this paper first introduces the regret theory to depict the regret aversion of decision-makers, and proposes the fair regret cross-efficiency aggregation (FRCEA) method (Method 1). Then the upper and lower limits of the fair regret interval cross-efficiency (FRICE) are calculated, and parameters reflecting the preferences of decision-makers are introduced. Next, this paper puts forth a consensus cross-efficiency aggregation (CCEA) method (Method 2) based on the efficiency expectations of DMUs and the actual aggregation results. By creating a fair evaluation environment, this paper aims to enable all DMUs to participate in the efficiency evaluation and accept the results, reaching a final consensus. Finally, the effectiveness and rationality of the methods above are verified after evaluating the academic research efficiencies of 13 prestigious universities in China.

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (72171052; 72371077), the Higher School Excellent Young Talent Support Project of Anhui Province (gxyqZD2020105), the Talent Research Start-up Fund project of Tongling University (2021tlxyrc20), the Excellent Youth Research Projects in Universities of Anhui Province (2024AH030083), the Doctoral Initiation Fund Project of Chongqing Normal University (No. 23XWB008).

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Authors and Affiliations

  1. School of Architecture and Engineering, Tongling University, Tongling, 244061, People’s Republic of China

    Xing-Xian Zhang

  2. Decision Sciences Institute, Fuzhou University, Fuzhou, 350116, People’s Republic of China

    Lei Chen & Ying-Ming Wang

  3. School of Economics and Management, Chongqing Normal University, Chongqing, 401331, People’s Republic of China

    Xu Wang

  4. Digital Intelligence Management Research Institute, Shanghai University of Finance and Economics Zhejiang College, Jinhua, 321015, People’s Republic of China

    Wenjin Zuo & Lijun Liu

  5. Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou, 350116, People’s Republic of China

    Ying-Ming Wang

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  1. Xing-Xian Zhang
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Correspondence to Lijun Liu.

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Zhang, XX., Chen, L., Wang, X. et al. A new cross-efficiency aggregation in data envelopment analysis: considering fairness mentality and group consensus. Oper Res Int J 25, 28 (2025). https://doi.org/10.1007/s12351-025-00904-6

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