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DEA by sequential exclusion of alternatives in heterogeneous samples

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  • Fuad Aleskerov

    (Faculty of Economic Sciences, Department of Mathematics, National Research University Higher School of Economics, 20 Myasnickaya Str., Moscow 101000, Russia2Institute of Control Science of Russian Academy of Sciences, 65 Profsouznaya Str., Moscow 117997, Russia)

  • Vsevolod Petrushchenko

    (International Laboratory of Decision Choice and Analysis, National Research University Higher School of Economics, 20 Myasnickaya Str., Moscow 101000, Russia)

Abstract

Data Envelopment Analysis (DEA) is a well-known nonparametric technique of efficiency evaluation which is actively used in many economic applications. However, DEA is not very well applicable when a sample consists of firms operating under drastically different conditions. We offer a new method of efficiency estimation in heterogeneous samples based on a sequential exclusion of alternatives and standard DEA approach. We show a connection between efficiency scores obtained via standard DEA model and the ones obtained via our algorithm. We also illustrate our model by evaluating 28 Russian universities and compare the results obtained by two techniques.

Suggested Citation

  • Fuad Aleskerov & Vsevolod Petrushchenko, 2016. "DEA by sequential exclusion of alternatives in heterogeneous samples," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(01), pages 5-22, January.
    • Handle: RePEc:wsi:ijitdm:v:15:y:2016:i:01:n:s021962201550042x
    DOI: 10.1142/S021962201550042X
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    References listed on IDEAS

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    Cited by:

    1. Irina V. Abankina & Fuad T. Aleskerov & Veronika Yu. Belousova & Leonid M. Gokhberg & Kirill V. Zinkovsky & Sofya G. Kiselgof & Vsevolod Petrushchenko & Sergey V. Shvydun, 2015. "Performance-Based Typology Of Universities: Evidence From Russia," HSE Working papers WP BRP 33/STI/2015, National Research University Higher School of Economics.
    2. Tien-Hsiang Chang & Ling-Jing Kao & Tsung-Yin Ou & Hsin-Pin Fu, 2018. "A Hybrid Method to Measure the Operational Performance of Fast Food Chain Stores," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1269-1298, July.
    3. Y. c{C}inar, 2016. "Research and Teaching Efficiencies of Turkish Universities with Heterogeneity Considerations: Application of Multi-Activity DEA and DEA by Sequential Exclusion of Alternatives Methods," Papers 1701.07318, arXiv.org.

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