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Merging two-stage series network structures: A DEA-based approach

Author

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  • Mohammad Khoveyni

    (Islamic Azad University)

  • Robabeh Eslami

    (South Tehran Branch, Islamic Azad University)

Abstract

Merging decision-making units (DMUs) is one of the most important issues in data envelopment analysis (DEA). Hitherto, several merging approaches have been presented in DEA; however, none of them can be used in network DEA. Because they do not consider intermediate products of two-stage DMUs (or two-stage processes) in the merging process. To tackle this problem, this study contributes to network DEA by introducing a novel merging approach. In this approach, we first survey the situations of the first and second stages of the candidate two-stage DMUs relative to the efficient frontiers and then obtain the merged two-stage DMU based on these situations. In other words, our proposed approach estimates the appropriate inputs and intermediate products for merging the candidate two-stage DMUs so that the merged two-stage DMU gets its favorable efficiency score. This research also explains the managerial and economic implications of merging two-stage DMUs. Finally, a numerical example and an empirical application to the US commercial banks are provided to show the use of the proposed approach.

Suggested Citation

  • Mohammad Khoveyni & Robabeh Eslami, 2022. "Merging two-stage series network structures: A DEA-based approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 273-302, March.
    • Handle: RePEc:spr:orspec:v:44:y:2022:i:1:d:10.1007_s00291-021-00653-w
    DOI: 10.1007/s00291-021-00653-w
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    Cited by:

    1. Alireza Moradi & Saber Saati & Mehrzad Navabakhsh, 2023. "Genetic algorithms for optimizing two-stage DEA by considering unequal intermediate weights," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1202-1217, September.

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