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Identifying outstanding units in centralized systems: A DEA approach.
Zahra Cheraghali1, Mohsen Rostamy-Malkhalifeh2
1Department of Applied Mathematics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran.
Plos One
|May 14, 2026
Summary
This study introduces a new Data Envelopment Analysis (DEA) model to identify top-performing decision-making units (DMUs) in centralized organizations. The model avoids constants, ensuring reliable results for efficiency analysis.
Area of Science:
- Operations Research
- Management Science
- Industrial Engineering
Background:
- Centralized organizations manage multiple Decision-Making Units (DMUs).
- Improving system efficiency requires identifying impactful DMUs.
- Traditional Data Envelopment Analysis (DEA) often focuses on local, not collective, DMU efficiency.
Purpose of the Study:
- To develop a novel DEA model for selecting a subset of 'k' outstanding DMUs in centralized systems.
- To overcome limitations of existing models, such as reliance on predefined constants.
- To enhance the robustness and interpretability of performance evaluation.
Main Methods:
- A new DEA-based mixed-integer nonlinear programming model is proposed.
- The model identifies 'k' outstanding DMUs from 'n' total units.
- It eliminates the need for predefined constants, ensuring feasibility and boundedness.
Main Results:
- The proposed model successfully identifies outstanding DMUs without requiring predefined constants.
- It guarantees feasible and bounded solutions, improving model reliability.
- Validation through two empirical studies confirms its practical applicability.
Conclusions:
- The new DEA model offers a robust and interpretable method for identifying key DMUs in centralized systems.
- It provides a practical decision-support tool for managers.
- This approach enhances the collective efficiency assessment of DMUs.
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