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Related Experiment Video

Updated: Jan 20, 2026

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
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Reconciled multiplicative relational two-stage network data envelopment analysis.

M Burak Erturan1

  • 1Dr.,Head Supply Engineer, General Directorate of State Hydraulic Works, Directorate of Region 13, Barış Mah. Halide Edip Cad. Kepez Antalya, Turkiye.

Methodsx
|January 19, 2026
PubMed
Summary
This summary is machine-generated.

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This study introduces the Reconciled Multiplicative Relational (RMR) model for two-stage systems. RMR offers a unique efficiency assessment solution, overcoming limitations of previous data envelopment analysis methods.

Area of Science:

  • Operations Research
  • Management Science
  • Industrial Engineering

Background:

  • Two-stage network systems require specialized efficiency assessment methods.
  • Traditional multiplicative relational models in Data Envelopment Analysis (DEA) can suffer from non-unique efficiency solutions.
  • Existing models often prioritize sub-processes, which may not reflect true system performance.

Purpose of the Study:

  • To present a novel methodology for fairer efficiency assessment in two-stage systems.
  • To address the non-uniqueness problem in multiplicative relational DEA models.
  • To introduce a model that does not prioritize any sub-process.

Main Methods:

  • Development of the Reconciled Multiplicative Relational (RMR) model.
  • Application of data reconciliation techniques within a relational DEA framework.
Keywords:
Data envelopment analysisData reconciliationEfficiencyMultiplicativeRelationalTwo-stage network DEA

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  • Simultaneous determination of maximum efficiency values for all processes under relational constraints.

    • Main Results:

    • The RMR model provides a unique efficiency assessment solution.
    • The methodology overcomes the non-uniqueness issue inherent in some relational DEA models.
    • The RMR model allows for simultaneous efficiency evaluation without process prioritization.

    Conclusions:

    • The RMR model offers a fairer and more robust efficiency assessment for two-stage systems.
    • This approach is particularly useful when no Decision Making Units (DMUs) are preferred or prior information is unavailable.
    • The RMR model enhances the applicability of relational DEA in complex operational environments.