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    A novel ranking method in data envelopment analysis: a real case on Chinese banking industry
    (Emerald Publishing, 2024) Nematizadeh, Maryeh; Amirteimoori, Alireza; Kordrostami, Sohrab; Khoshandam, Leila
    Purpose: This study aims to address the lack of discrimination between fully efficient decision-making units in nonparametric efficiency analysis models by introducing a new ranking technique that incorporates contextual variables. Design/methodology/approach: The proposed method combines Data Envelopment Analysis (DEA) and Ordinary Least Squares (OLS). First, DEA evaluates the partial efficiency of each unit, considering all inputs and only one output. Next, OLS removes the influence of contextual variables on the partial efficiencies. Finally, a ranking criterion based on modified partial efficiencies is formulated. The method is applied to data from 100 Chinese banks, including state-owned, commercial and industrial institutions, for the year 2020. Findings: The ranking results show that the top six positions are assigned to highly esteemed banks in China, demonstrating strong alignment with real-world performance. The method provides a comprehensive ranking of all units, including nonextreme efficient ones, without excluding any. It resolves infeasibility issues that arise during the ranking of efficient units and ensures uniqueness in efficiency scores, leading to a more reliable and robust ranking process. Contextual variables exerted a greater influence on the first partial efficiency compared to the second. Notably, Total Capital Adequacy (TCA) significantly impact bank efficiency. Originality/value: This study introduces a novel ranking method that effectively integrates contextual variables into DEA-based efficiency analysis, addressing limitations of existing methods. The practical application to Chinese banks demonstrates its utility and relevance. © 2024, Emerald Publishing Limited.
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    An efficiency score unification method in data envelopment analysis using slack-based models with application in banking
    (Elsevier inc, 2025) Hadi, Ali; Amirteimoori, Alireza; Kordrostami, Sohrab; Mehrabian, Saeid
    Providing a unique estimation model of the efficiency score for a bank branch has long been a primary concern for bank managers, who frequently reject efficiency studies because they contend that a single perspective evaluation cannot adequately display the multifunctional nature of decision-making units (DMUs). This paper presents a unification model for efficiency scores in the banking industry. The proposed model evaluates the efficiency of decision-making units through a two-stage method from different perspectives. This study calculates efficiency scores from several aspects and various inputs/outputs in the first stage, so an expanded space is used in the second stage. All viewpoints are transferred into a new space, creating a new efficient frontier in the expanded space. This model presents the unified efficiency score from DMUs by applying the slack-based model (SBM), which proposes enhancement guidelines. A unified efficiency score is created by considering three perspectives: production, profitability, and intermediary. Unlike the average score, the results show that the unified efficiency score can reflect the performance difference between the three scores achieved from the three perspectives. Additionally, this method demonstrates that DMUs cannot achieve overall efficiency if they are inefficient in at least one of the three aspects.
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    An inverse stochastic two-stage DEA model to deal with resource planning
    (AMER INST MATHEMATICAL SCIENCES-AIMS, 2025) Vishghaei, Yasaman Zibaei; Kordrostami, Sohrab; Amirteimoori, Alireza; Shokri, Soheil
    Resource planning is a significant aspect in organizations with particularly complex structures and uncertain data. Accordingly, an inverse stochastic network data envelopment analysis (ISNDEA) approach is proposed in this research to estimate the changes of stochastic inputs of two-stage processes for the perturbations of stochastic desirable outputs of stages one and two while the stochastic overall and stage efficiencies are preserved. The introduced ISNDEA model is a stochastic multi-objective optimization problem and it is transformed into a deterministic linear framework. Stochastic undesirable outputs are also included in the investigation due to their presence in many real cases. A real-world examination of the banking sector is presented to show the applicability of the planned technique. The results denote the proposed approach is advantageous to plan the resources of two-stage processes with stochastic data and undesirable outputs.
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    Efficiency analysis in bi-level on fuzzy input and output
    (Elsevier inc., 2025) Ghaziyani, Kh; Lotfi, F. Hosseinzadeh; Kordrostami, Sohrab; Amirteimoori, Alireza
    To enhance the conventional framework of data envelope analysis (DEA), a novel hybrid bi-level model is proposed, integrating fuzzy logic with triangular fuzzy numbers to effectively address data uncertainty. This model innovatively departs from the traditional DEA's 'black box' approach by incorporating inter-organizational relationships and the internal dynamics of decision-making units (DMUs). Utilizing a modified Russell's method, it provides a nuanced efficiency analysis in scenarios of ambiguous data. The study aims to enhance the accuracy and applicability of Data Envelopment Analysis in uncertain data environments. To achieve this, a novel hybrid bi-level model integrating fuzzy logic is presented. Validated through a case study involving 15 branches of a private Iranian bank, the model demonstrates improved accuracy in efficiency assessments and paves the way for future research in operational systems uncertainty management. The results indicated that, among the 15 branches of a private Iranian bank analyzed for the year 2022, branches 1, 10, and 11 demonstrated leader-level efficiency, while branch 3 exhibited follower-level efficiency, and branch 1 achieved overall efficiency. These branches attained an efficiency rating of E++, signifying a high level of efficiency within the model's parameters.
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    Improving decision-making units in performance analysis methods: a data envelopment analysis approach
    (Springer Heidelberg, 2023) Amirteimoori, Alireza; Allahviranloo, Tofigh; Kordrostami, Sohrab; Bagheri, Seyed Fatemeh
    Classifying decision-making units into efficient and inefficient classes is a common procedure in nonparametric data envelopment analysis approach. The inefficient units can be projected onto the production frontier by decreasing their inputs or increasing their outputs. However, if the closer projection point is clarified, the units will achieve their best situation. Previous methods have only focused on one objective, and other features have been ignored. This paper presents an alternative definition for the best projection by considering three main aspects: cost, revenue and closest projection points. The proposed procedure provides the closest possible distance, the lowest cost and the highest revenue, simultaneously. The goal programming has been used in this model. The results of implementing this approach on China's textile industry have shown the model applicability.
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    An inverse multi-period FDH model with undesirable outputs
    (Croatian Operational Research Soc, 2023) Asadi, Farzaneh; Kordrostami, Sohrab; Amirteimoori, Alireza; Noveiri, Monireh Jahani Sayyad
    In some examinations, the changes in performance measures and the efficiency of entities should be addressed over a span of time despite the undesirable outputs and unsatisfactory convexity property. In this study, the performance of processes is analyzed over several periods of time by presenting a multi-period model based on the free disposal hull (FDH) approach, incorporating undesirable outputs. Using the product of availability, performance (efficiency) and quality, the overall equipment effectiveness (OEE) is calculated which shows the level of productivity. After estimating the performance and OEE, an inverse multi-period FDH model is introduced to measure the input changes for the changes made to outputs in different time periods. The proposed approaches are used in the automotive industry to analyze the performance and changes in input measures over multiple periods of time. The results show that the proposed technique is reasonable for assessing the multi-period efficiency, the period and overall OEE of the systems, and the input changes related to several periods while the convexity assumption is violated.