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

Kefu Yi et al.

Financial Innovation2026https://doi.org/10.1186/s40854-025-00818-4article
AJG 2ABDC B
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0.50

Abstract

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.

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https://doi.org/https://doi.org/10.1186/s40854-025-00818-4

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@article{kefu2026,
  title        = {{Optimizing resource allocation in a three-stage banking network: a centralized DEA approach with shared, integer-valued and undesirable factors}},
  author       = {Kefu Yi et al.},
  journal      = {Financial Innovation},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1186/s40854-025-00818-4},
}

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0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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