利用负数据推进 DEA 中的集团效率评估:银行业的经验应用

Leila Kolahdoozi, Reza Kazemi Matin, G. Tohidi, S. Razavyan
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引用次数: 0

摘要

数据包络分析法(DEA)在评估生产单位效率方面发挥着举足轻重的作用。本研究利用专为处理负数据而设计的修正半定向径向测量(MSORM)模型,扩展了银行业的集团效率评估。它引入了两种不同的效率定义,并开发了在这些群体中对其进行评估的模型。MSORM 模型以银行为决策单元,深入研究了集团效率的复杂性。通过有效解决负面数据的复杂性,该模型能够在各种群体框架内对银行效率进行全面评估。本研究进一步探讨了 MSORM 框架内基于平均和最弱表现的效率定义的有效性。实证研究结果表明,不同范式下的集团效率评估存在显著差异,凸显了评估方法的影响。这项研究有助于深入了解银行业内部的绩效差异,并有助于加强银行系统的效率评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancing group efficiency evaluation in DEA with negative data: An empirical application in the banking industry
Data Envelopment Analysis (DEA) plays a pivotal role in assessing production unit efficiency. This study extends group efficiency assessment within the banking sector by utilizing the Modified Semi-Oriented Radial Measure (MSORM) model, specifically designed to handle negative data. It introduces two distinct efficiency definitions and develops models for their evaluation within these groups. Focusing on banks as decision-making units, the MSORM model delves into the intricacies of group efficiency. By effectively addressing negative data complexities, it enables a comprehensive evaluation of bank efficiency across various group frameworks. The study further examines the efficacy of efficiency definitions based on average and weakest performances within the MSORM framework. Empirical findings reveal significant variations in group efficiency assessment under different paradigms, highlighting the impact of the evaluation approach. This research contributes valuable insights into performance variations within the banking industry and aids in enhancing efficiency evaluations in banking systems.
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