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学者姓名：陈磊
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Abstract ：
As a direction selection in the direction distance function (DDF), endogenous DDF can accurately reflect the numerical characteristics of inputs/outputs, but it is difficult to effectively popularize. And it is also difficult to effectively combine with reality. To solve those problems, this paper introduces slack variables to construct a new endogenous direction-setting mechanism, which makes the endogenous model have the conditions to be popularized. Based on the original endogenous DDF, we consider environmental concern, economic concern, coordinated development, and priority development, and then construct six new extended DDF models with slack variables. Based on priority development, we further propose six new extended DDF models. These new extended models can not only realize the complete internalization of direction determination but also overcome the limitations of traditional endogenous models. Combined with the actual case, the emission reduction potential of different areas is revealed, and the improved path is proposed. The results show that the new extended DDF models effectively reflect the different development modes of carbon emissions, and different development modes have a significant impact on emission reduction potential. In addition, compared with economic concern and priority development, coordinated development and environmental concern are most beneficial to carbon emission reduction, but the development mode of environmental concern can better reveal the improved path of environmental development.
Keyword ：
emission reduction potential emission reduction potential endogenous DDF endogenous DDF extended DDF models extended DDF models improved path improved path slack variables slack variables
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| GB/T 7714 | Wang, Junchao , Ye, Jun-Hong , Chen, Lei . A New Endogenous Direction Selection Mechanism for the Direction Distance Function Method Applied to Different Economic-Environmental Development Modes [J]. | SUSTAINABILITY , 2025 , 17 (7) . |
| MLA | Wang, Junchao 等. "A New Endogenous Direction Selection Mechanism for the Direction Distance Function Method Applied to Different Economic-Environmental Development Modes" . | SUSTAINABILITY 17 . 7 (2025) . |
| APA | Wang, Junchao , Ye, Jun-Hong , Chen, Lei . A New Endogenous Direction Selection Mechanism for the Direction Distance Function Method Applied to Different Economic-Environmental Development Modes . | SUSTAINABILITY , 2025 , 17 (7) . |
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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.
Keyword ：
Cross-efficiency evaluation Cross-efficiency evaluation Data envelopment analysis Data envelopment analysis Fairness mentality Fairness mentality Group consensus Group consensus Regret theory Regret theory
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| GB/T 7714 | Zhang, Xing-Xian , Chen, Lei , Wang, Xu et al. A new cross-efficiency aggregation in data envelopment analysis: considering fairness mentality and group consensus [J]. | OPERATIONAL RESEARCH , 2025 , 25 (2) . |
| MLA | Zhang, Xing-Xian et al. "A new cross-efficiency aggregation in data envelopment analysis: considering fairness mentality and group consensus" . | OPERATIONAL RESEARCH 25 . 2 (2025) . |
| APA | Zhang, Xing-Xian , Chen, Lei , Wang, Xu , Zuo, Wenjin , Liu, Lijun , Wang, Ying-Ming . A new cross-efficiency aggregation in data envelopment analysis: considering fairness mentality and group consensus . | OPERATIONAL RESEARCH , 2025 , 25 (2) . |
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The efficiency decomposition and frontier projection of traditional two-stage network data envelopment analysis (DEA) model under variable returns to scale (VRS) are often not equivalent; which not only contradicts DEA theory, but also reduces the scientificity of the model. The main reason for this inequivalence is that there is a synergistic effect of variable scale return in two different stages. Therefore, this paper describes the production frontier of two-stage DEA under VRS for analyzing this synergistic effect, and then the efficiency evaluation pitfalls of two-stage DEA under VRS are identified. From the input orientation, output orientation, non- orientation perspectives, different two-stage network DEA models under VRS are respectively constructed to solve these evaluation pitfalls, and the equivalence relationships of their multiplier model and envelopment model are proved; and then the efficiency decomposition and frontier projection with equivalence relationship can be obtained to meet the different needs of decision-makers. Furthermore, variable intermediate element is discussed in the non-orientation model for achieving the Pareto optimality of two stages during the process of efficiency decomposition and frontier projection. By these models, the theoretical foundation of two-stage network DEA under VRS has been further improved. Finally, two examples are provided to illustrate the effectiveness of the new models.
Keyword ：
Data envelopment analysis Data envelopment analysis Efficiency decomposition Efficiency decomposition Equivalence relationship Equivalence relationship Frontier projection Frontier projection Two-stage network Two-stage network Variable returns to scale Variable returns to scale
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| GB/T 7714 | Chen, Lei , Wang, Ying-Ming . Efficiency decomposition and frontier projection of two-stage network DEA under variable returns to scale [J]. | EUROPEAN JOURNAL OF OPERATIONAL RESEARCH , 2025 , 322 (1) : 157-170 . |
| MLA | Chen, Lei et al. "Efficiency decomposition and frontier projection of two-stage network DEA under variable returns to scale" . | EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 322 . 1 (2025) : 157-170 . |
| APA | Chen, Lei , Wang, Ying-Ming . Efficiency decomposition and frontier projection of two-stage network DEA under variable returns to scale . | EUROPEAN JOURNAL OF OPERATIONAL RESEARCH , 2025 , 322 (1) , 157-170 . |
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Considering internal operation of decision-making unit (DMU) while introducing technical heterogeneity is the advantage of two-stage meta-frontier data envelopment analysis (DEA) method. However, each DMU can obtain double shared ratios in different technical environments, and each DMU must ultimately determine one shared ratio under actual decision-making, which leads to a decision-making dilemma of two-stage meta-frontier DEA in application. Therefore, based on traditional shared ratio selection, some double shared ratio selection methods of dominant, autonomous and coordinated are proposed for different decision-making needs, which promote deep integration of meta-frontier and two-stage DEA, and thus provide clear and specific shared ratio selections for decision makers. In addition, to overcome the limitations of double shared ratio selection, this paper takes double shared ratios as a selection interval and further extends double shared ratio selection methods, enhancing the flexibility of shared ratio selection. Furthermore, different double shared ratio selections are divided into uniform and non-uniform for comparative analysis. This paper indicates that: (1) The degree of concentration in DMU shared ratio selection is positively correlated with efficiency. (2) Unifying the shared ratios for meta-frontier and group frontier is beneficial for improving overall efficiency level.
Keyword ：
Data envelopment analysis Data envelopment analysis Meta-frontier Meta-frontier Shared ratio Shared ratio Two-stage network Two-stage network
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| GB/T 7714 | Guo, Xu , Chen, Lei . Double shared ratio selection of two-stage meta-frontier DEA methods based on shared input [J]. | COMPUTATIONAL & APPLIED MATHEMATICS , 2025 , 44 (6) . |
| MLA | Guo, Xu et al. "Double shared ratio selection of two-stage meta-frontier DEA methods based on shared input" . | COMPUTATIONAL & APPLIED MATHEMATICS 44 . 6 (2025) . |
| APA | Guo, Xu , Chen, Lei . Double shared ratio selection of two-stage meta-frontier DEA methods based on shared input . | COMPUTATIONAL & APPLIED MATHEMATICS , 2025 , 44 (6) . |
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Supply chain alliance cooperation is of great significance to optimize resource allocation and improve profits, but the impact of resource allocation efficiency on profits has not been quantitatively studied, and the profit loss caused by resource allocation inefficiency has not been attention and improved. Therefore, based on hybrid network DEA, this paper proposes a new method to measure resource allocation efficiency from the perspective of profit, which quantifies the profit loss caused by resource allocation inefficiency for the first time. To reduce profit loss, multi-output and multi-input technical bias method (MMTB) is proposed to guide the rearrangement of upstream and downstream structures in supply chain alliances, so as to accurately find structural rearrangement plan under profit maximization, and then realize the adjustment of profit loss. On this basis, a new classification method of profit loss (adjustable profit loss and unadjusted profit loss) and a new efficiency measurement method (profit adjustable efficiency) are proposed. Finally, we analyze the data of 25 supply chains in resin producing companies to verify our proposed method. The resulting resource allocation inefficiency is compared with the classical method. © 2025 Elsevier Ltd
Keyword ：
Efficiency Efficiency Losses Losses Profitability Profitability Resource allocation Resource allocation Supply chains Supply chains
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| GB/T 7714 | Guo, Xu , Chen, Lei . Internal mechanism of resource allocation efficiency and profit level in supply chain alliance: New evaluation, classification and adjustment methods [J]. | Computers and Industrial Engineering , 2025 , 208 . |
| MLA | Guo, Xu et al. "Internal mechanism of resource allocation efficiency and profit level in supply chain alliance: New evaluation, classification and adjustment methods" . | Computers and Industrial Engineering 208 (2025) . |
| APA | Guo, Xu , Chen, Lei . Internal mechanism of resource allocation efficiency and profit level in supply chain alliance: New evaluation, classification and adjustment methods . | Computers and Industrial Engineering , 2025 , 208 . |
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Inverse data envelopment analysis (DEA), which is an effective tool for determining inputs and outputs, is commonly applied in areas such as output prediction, resource allocation, and target setting. However, existing inverse DEA methods typically assume precise and deterministic data, which limits applicability in uncertain production environments, particularly when both random and fuzzy environments are present. This study introduces a novel inverse DEA approach for optimizing inputs and outputs in mixed uncertainty environments. The proposed model allows decision-makers to achieve target efficiency and meet various input/output targets under different production scale assumptions. First, a new optimality principle for multi-objective fuzzy random problems is presented and the necessary theoretical conditions for input/output calculations are derived. Second, an equivalent linear model is introduced to solve the inverse DEA problem with fuzzy random variables, thereby overcoming the challenges associated with nonlinear programming. Notably, the proposed model offers enhanced flexibility as it does not rely on specific fuzzy numbers or predefined assumptions regarding random distributions. Finally, the effectiveness of the model is validated through numerical examples and a case study, demonstrating its practical application in complex decision-making scenarios.
Keyword ：
Fuzzy random variable Fuzzy random variable Inverse data envelopment analysis Inverse data envelopment analysis Mixed uncertainty Mixed uncertainty Multi-objective programming Multi-objective programming
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| GB/T 7714 | Huang, Lizhen , Chen, Lei . Fuzzy random multi-objective optimization using a novel mixed fuzzy random inverse DEA model in input-output production [J]. | JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS , 2025 , 470 . |
| MLA | Huang, Lizhen et al. "Fuzzy random multi-objective optimization using a novel mixed fuzzy random inverse DEA model in input-output production" . | JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 470 (2025) . |
| APA | Huang, Lizhen , Chen, Lei . Fuzzy random multi-objective optimization using a novel mixed fuzzy random inverse DEA model in input-output production . | JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS , 2025 , 470 . |
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Standardized evaluation has been applied in the research and development (R&D) activities of Chinese universities for a long time, which ignores the technological heterogeneity between these activities. Standardized evaluation has thus been difficult to meet the evaluation needs of the Chinese government, and classified evaluation is imperative for the diversified development of R&D activities in Chinese universities. Therefore, this paper introduces directional distance function (DDF) model with endogenous technique into meta-frontier data envelopment analysis framework to construct a new theoretical tool of classified evaluation, and this new method is applied to evaluate the efficiency of R&D activities of 939 Chinese universities. The theoretical contribution is to unify the endogenous directions relative to different frontiers, and then a new meta-frontier DDF framework is constructed; while the practical contribution is to provide the following conclusions and implications: (1) classified evaluation and standardized evaluation have different applicability to different categories of Chinese universities; (2) the homogeneity of the improvement direction is serious in Chinese universities; (3) different categories of Chinese universities have different improvement needs in different inputs and outputs, and the distances between most universities and their two frontiers are not far; (4) the selections of both improvement direction and indicator are important factors affecting the evaluation results. Finally, some useful suggestions are provided to improve the efficiency of R&D activities in Chinese universities.
Keyword ：
Chinese universities Chinese universities Classified evaluation Classified evaluation Directional distance function Directional distance function Efficiency Efficiency Technological heterogeneity Technological heterogeneity
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| GB/T 7714 | Chen, Lei , Luo, Cuiyun , Liao, Li-Huan et al. Classified evaluation of R&D activities in Chinese universities: An application of new meta-frontier directional distance function framework [J]. | TECHNOLOGY IN SOCIETY , 2024 , 78 . |
| MLA | Chen, Lei et al. "Classified evaluation of R&D activities in Chinese universities: An application of new meta-frontier directional distance function framework" . | TECHNOLOGY IN SOCIETY 78 (2024) . |
| APA | Chen, Lei , Luo, Cuiyun , Liao, Li-Huan , Wang, Suhui . Classified evaluation of R&D activities in Chinese universities: An application of new meta-frontier directional distance function framework . | TECHNOLOGY IN SOCIETY , 2024 , 78 . |
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The convexity of meta-frontier is a debated topic in data envelopment analysis (DEA). This paper claims that meta-frontier is a non-convex hull, but the production activities between the non-convex meta-frontier and the convex traditional production frontier may be feasible. Therefore, technology compatibility is defined to explain this feasibility, and a modified DEA model is constructed to evaluate the efficiency of decision-making units with technology heterogeneity and technology compatibility. Sequentially, two new meta-frontier DEA frameworks are constructed to evaluate and decompose efficiency, thereby revealing the impact of technology heterogeneity and technology compatibility on efficiency. In addition, a series of discussions are presented to analyze these two new frameworks.
Keyword ：
Convexity Convexity Data envelopment analysis Data envelopment analysis Meta-frontier Meta-frontier Technology compatibility Technology compatibility Technology heterogeneity Technology heterogeneity
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| GB/T 7714 | Chen, Lei , Lan, Yi-Xin , Wang, Suhui . Convex or non-convex? A new meta-frontier data envelopment analysis framework considering technology compatibility [J]. | OR SPECTRUM , 2024 , 47 (1) : 325-346 . |
| MLA | Chen, Lei et al. "Convex or non-convex? A new meta-frontier data envelopment analysis framework considering technology compatibility" . | OR SPECTRUM 47 . 1 (2024) : 325-346 . |
| APA | Chen, Lei , Lan, Yi-Xin , Wang, Suhui . Convex or non-convex? A new meta-frontier data envelopment analysis framework considering technology compatibility . | OR SPECTRUM , 2024 , 47 (1) , 325-346 . |
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Compared with two-level meta-frontier, three-level meta-frontier can have more projection direction to select. However, at present, three-level meta-frontier framework mainly adopts the traditional exogenous projection, which makes it continue the defects of two-level meta-frontier, that is, in the non-radial data envelopment analysis (DEA) model, there may be an unreasonable technology gap ratio (TGR), which is not conducive to effectively evaluating the efficiency of decision-making units (DMUs). By decomposing the projection process, the combined projection method is proposed to solve the above problems. In the selection of projection direction, the selection methods of layer-by-layer accumulation projection (LA) and accumulation consistency projection (AC) are proposed, and thus some new combined projection methods are established. In addition, the improvement of projection methods in two-level meta-frontier are introduced into three-level meta-frontier, and then different combined projection methods are compared. A numerical example and an empirical application are given to compare different combined projection methods, and the results support the use of our proposed combined projection methods.
Keyword ：
Combined projection Combined projection Data envelopment analysis Data envelopment analysis Technology gap ratio Technology gap ratio Three-level meta-frontier Three-level meta-frontier
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| GB/T 7714 | Guo, Xu , Chen, Lei . Extension and improvement of three-level meta-frontier framework based on multiple combined projection methods [J]. | COMPUTATIONAL & APPLIED MATHEMATICS , 2024 , 43 (5) . |
| MLA | Guo, Xu et al. "Extension and improvement of three-level meta-frontier framework based on multiple combined projection methods" . | COMPUTATIONAL & APPLIED MATHEMATICS 43 . 5 (2024) . |
| APA | Guo, Xu , Chen, Lei . Extension and improvement of three-level meta-frontier framework based on multiple combined projection methods . | COMPUTATIONAL & APPLIED MATHEMATICS , 2024 , 43 (5) . |
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Unlike most existing clustering methods, data envelopment analysis (DEA) clusters decisionmaking units (DMUs) based on production characteristics rather than distance. The clustering results obtained using the DEA clustering approach reflect the production relationship between the inputs and outputs of the DMUs to better identify the inherent production correlation between them. However, existing DEA-based clustering approaches struggle to rationally assign unique clusters to DMUs that exhibit multiple production characteristics and lack the further processing of clustering results. Therefore, this study proposes a new DEA clustering approach based on the individual perspective of DMUs that incorporates prospect theory to reflect the individual preferences of DMUs to assign each DMU to a relatively unique cluster. Furthermore, a clustering adjustment method and a clustering reduction method are proposed to further improve the clustering quality. The former can handle some special clusters according to the decision-maker ' s preference, and the latter permits the realization of an arbitrary number of clusters. The new DEA clustering approach is more reliable and flexible, and more valuable information can be provided for decision-makers. Finally, the validity of the new approach is verified through a comparison with existing approaches in two numerical cases, and an empirical example is used to illustrate its practicability.
Keyword ：
Clustering Clustering Data envelopment analysis Data envelopment analysis Individual perspective Individual perspective Production relationship Production relationship Prospect theory Prospect theory
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| GB/T 7714 | Chen, Lei , Fan, Minghuan , Wang, Junchao . A controlled data envelopment analysis clustering approach based on individual perspective [J]. | INFORMATION SCIENCES , 2024 , 677 . |
| MLA | Chen, Lei et al. "A controlled data envelopment analysis clustering approach based on individual perspective" . | INFORMATION SCIENCES 677 (2024) . |
| APA | Chen, Lei , Fan, Minghuan , Wang, Junchao . A controlled data envelopment analysis clustering approach based on individual perspective . | INFORMATION SCIENCES , 2024 , 677 . |
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