Scholarlink

<p>Resource allocation is a critical challenge in the banking sector. This research introduces an innovative centralized resource allocation model based on data envelopment analysis (DEA) designed for a three-stage network production system. The model incorporates shared inputs, integer-valued data, and undesirable outputs, providing a comprehensive framework to address the complexities of banking operations. We establish an axiomatic production technology set for this three-stage network, which forms the basis for our enhanced Russell method-based model. The effectiveness of the proposed model is demonstrated through a case study of 45 bank branches in West Azerbaijan Province, Iran, covering the stages of "Internet banking," "production," and "profitability." By applying this model to real-world data, we illustrate its practical utility in achieving precise resource allocation and setting benchmarks to improve operational performance. Furthermore, we use the Li test to show that the hypothesis of similarity in target setting and benchmarking between the proposed DEA approach and traditional methods—considering the effects of integrality and undesirable factor assumptions—is rejected. This study not only offers a novel approach to resource allocation but also demonstrates its applicability in practical banking scenarios.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Optimizing resource allocation in a three-stage banking network: a centralized DEA approach with shared, integer-valued and undesirable factors

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月2日

查看全文
  • Kefu Yi,
  • Amir Hossein Yadollahi,
  • Reza Kazemi Matin

摘要

Resource allocation is a critical challenge in the banking sector. This research introduces an innovative centralized resource allocation model based on data envelopment analysis (DEA) designed for a three-stage network production system. The model incorporates shared inputs, integer-valued data, and undesirable outputs, providing a comprehensive framework to address the complexities of banking operations. We establish an axiomatic production technology set for this three-stage network, which forms the basis for our enhanced Russell method-based model. The effectiveness of the proposed model is demonstrated through a case study of 45 bank branches in West Azerbaijan Province, Iran, covering the stages of "Internet banking," "production," and "profitability." By applying this model to real-world data, we illustrate its practical utility in achieving precise resource allocation and setting benchmarks to improve operational performance. Furthermore, we use the Li test to show that the hypothesis of similarity in target setting and benchmarking between the proposed DEA approach and traditional methods—considering the effects of integrality and undesirable factor assumptions—is rejected. This study not only offers a novel approach to resource allocation but also demonstrates its applicability in practical banking scenarios.