基于启发式框架和动态数据包络Optimization方法的多分支银行效率评价：一个真实案例研究
Efficiency Evaluation of Banks with Many Branches using a Heuristic Framework and Dynamic Data Envelopment Optimization Approach: A Real Case Study
摘要：
评估组织和组织内分支机构的效率对管理人员来说是一个具有挑战性的问题。评价标准允许组织对其内部单位进行排名，确定其相对于竞争对手的位置，并实施改进和发展战略。在银行分支机构绩效评价的众多方法中，非参数方法近年来引起了研究者的关注。最广泛使用的非参数方法之一是数据包络分析（DEA），它导致了有希望的结果。然而，静态DEA方法没有考虑模型中的时间。因此，本文使用动态DEA（DDEA）方法来评估伊朗一家私人银行三年（2017 - 2019年）的分支机构。然后将结果与静态DEA进行比较。在对分支进行排序之后，使用K-means方法对它们进行聚类。最后，一个全面的灵敏度分析的方法，以帮助管理人员决定改变变量，以转移一个分支机构从一个集群到一个更有效的。
英文摘要：
Evaluating the efficiency of organizations and branches within an organization is a challenging issue for managers. Evaluation criteria allow organizations to rank their internal units, identify their position concerning their competitors, and implement strategies for improvement and development purposes. Among the methods that have been applied in the evaluation of bank branches, non-parametric methods have captured the attention of researchers in recent years. One of the most widely used non-parametric methods is the data envelopment analysis (DEA) which leads to promising results. However, the static DEA approaches do not consider the time in the model. Therefore, this paper uses a dynamic DEA (DDEA) method to evaluate the branches of a private Iranian bank over three years (2017-2019). The results are then compared with static DEA. After ranking the branches, they are clustered using the K-means method. Finally, a comprehensive sensitivity analysis approach is introduced to help the managers to decide about changing variables to shift a branch from one cluster to a more efficient one.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
