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Extended utility and DEA models without explicit input

Author

Listed:
  • Guoliang Yang

    (Institute of Policy and Management, Chinese Academy of Sciences, Beijing, China)

  • Wanfang Shen

    (Shandong University of Finance and Economics, Shandong, Jinan, China)

  • Daqun Zhang

    (Temple University, Philadelphia, USA)

  • Wenbin Liu

    (University of Kent, Canterbury, UK)

Abstract

In this paper, we discuss the relationship between multi-attribute utility theory and data envelopment analysis (DEA) models without explicit inputs (DEA-WEI), including dual models and some theoretical analysis of DEA-WEI models. We then propose generic DEA-WEI models with quadratic utility terms. Finally, we provide illustrative examples to show that DEA-WEI with suitable quadratic utility terms are able to reflect some value judgments that the standard DEA models cannot.

Suggested Citation

  • Guoliang Yang & Wanfang Shen & Daqun Zhang & Wenbin Liu, 2014. "Extended utility and DEA models without explicit input," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(8), pages 1212-1220, August.
    • Handle: RePEc:pal:jorsoc:v:65:y:2014:i:8:p:1212-1220
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    Cited by:

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    2. Nguyen, Trang Thi Thuy & Pham, Binh Thai & Prior, Diego & van Hemmen, Stefan, 2022. "Performance of tax simplification around the world: A panel frontier analysis," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    3. Giannis Karagiannis, 2017. "On aggregate composite indicators," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 741-746, July.
    4. Fernández-Macho, Javier & González, Pilar & Virto, Jorge, 2016. "An index to assess maritime importance in the European Atlantic economy," Marine Policy, Elsevier, vol. 64(C), pages 72-81.
    5. Cesaroni, Giovanni & Kerstens, Kristiaan & Van de Woestyne, Ignace, 2019. "Short- and long-run plant capacity notions: Definitions and comparison," European Journal of Operational Research, Elsevier, vol. 275(1), pages 387-397.
    6. Karagiannis, Giannis & Knox Lovell, C.A., 2016. "Productivity measurement in radial DEA models with a single constant input," European Journal of Operational Research, Elsevier, vol. 251(1), pages 323-328.
    7. Turkson, Charles & Liu, Wenbin & Acquaye, Adolf, 2024. "A data envelopment analysis based evaluation of sustainable energy generation portfolio scenarios," Applied Energy, Elsevier, vol. 363(C).
    8. Martin Boďa & David Cole & Mária Murray Svidroňová & Jolana Gubalová, 2022. "Prevailing narratives versus reality of a small and medium town decline in a CEE country," Operational Research, Springer, vol. 22(3), pages 3113-3145, July.
    9. Lahouel, Béchir Ben & Zaied, Younes Ben & Song, Yaoyao & Yang, Guo-liang, 2021. "Corporate social performance and financial performance relationship: A data envelopment analysis approach without explicit input," Finance Research Letters, Elsevier, vol. 39(C).
    10. Widarti Widarti & Desfitrina Desfitrina & Zulfadhli Zulfadhli, 2020. "Business Process Life Cycle Affects Company Financial Performance: Micro, Small, and Medium Business Enterprises During The Covid-19 Period," International Journal of Economics and Financial Issues, Econjournals, vol. 10(5), pages 211-219.
    11. Yang, Guoliang & Ahlgren, Per & Yang, Liying & Rousseau, Ronald & Ding, Jielan, 2016. "Using multi-level frontiers in DEA models to grade countries/territories," Journal of Informetrics, Elsevier, vol. 10(1), pages 238-253.
    12. Yang, Guo-liang & Yang, Jian-Bo & Xu, Dong-Ling & Khoveyni, Mohammad, 2017. "A three-stage hybrid approach for weight assignment in MADM," Omega, Elsevier, vol. 71(C), pages 93-105.

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