Efficiency analysis in bi-level on fuzzy input and output

IF 8.1 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS Information Sciences Pub Date : 2024-10-22 DOI:10.1016/j.ins.2024.121551
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Abstract

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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关于模糊输入和输出的双层效率分析
为了改进传统的数据包络分析(DEA)框架,我们提出了一种新颖的混合双层模型,将模糊逻辑与三角模糊数相结合,以有效解决数据的不确定性问题。该模型创新性地摆脱了传统 DEA 的 "黑箱 "方法,纳入了组织间关系和决策单元(DMU)的内部动态。利用改进的罗素方法,该模型可在数据模糊的情况下提供细致入微的效率分析。本研究旨在提高数据包络分析法在不确定数据环境中的准确性和适用性。为此,研究提出了一种融合模糊逻辑的新型混合双层模型。通过对伊朗一家私人银行的 15 家分行进行案例研究验证,该模型提高了效率评估的准确性,并为运营系统不确定性管理的未来研究铺平了道路。结果表明,在分析的伊朗一家私营银行的 15 家分行中,2022 年,1、10 和 11 分行的效率达到了领导者水平,3 分行的效率达到了追随者水平,1 分行的效率达到了整体水平。这些分行的效率评级为 E++,表明在模型参数范围内具有较高的效率水平。
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来源期刊
Information Sciences
Information Sciences 工程技术-计算机:信息系统
CiteScore
14.00
自引率
17.30%
发文量
1322
审稿时长
10.4 months
期刊介绍: Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
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