IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v202y2010i2p595-603.html
   My bibliography  Save this article

Cost efficiency measures in data envelopment analysis with data uncertainty

Author

Listed:
  • Mostafaee, A.
  • Saljooghi, F.H.

Abstract

This paper extends the classical cost efficiency (CE) models to include data uncertainty. We believe that many research situations are best described by the intermediate case, where some uncertain input and output data are available. In such cases, the classical cost efficiency models cannot be used, because input and output data appear in the form of ranges. When the data are imprecise in the form of ranges, the cost efficiency measure calculated from the data should be uncertain as well. So, in the current paper, we develop a method for the estimation of upper and lower bounds for the cost efficiency measure in situations of uncertain input and output data. Also, we develop the theory of efficiency measurement so as to accommodate incomplete price information by deriving upper and lower bounds for the cost efficiency measure. The practical application of these bounds is illustrated by a numerical example.

Suggested Citation

  • Mostafaee, A. & Saljooghi, F.H., 2010. "Cost efficiency measures in data envelopment analysis with data uncertainty," European Journal of Operational Research, Elsevier, vol. 202(2), pages 595-603, April.
    • Handle: RePEc:eee:ejores:v:202:y:2010:i:2:p:595-603
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(09)00448-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Schaffnit, Claire & Rosen, Dan & Paradi, Joseph C., 1997. "Best practice analysis of bank branches: An application of DEA in a large Canadian bank," European Journal of Operational Research, Elsevier, vol. 98(2), pages 269-289, April.
    2. Jahanshahloo, G.R. & Soleimani-damaneh, M. & Mostafaee, A., 2008. "A simplified version of the DEA cost efficiency model," European Journal of Operational Research, Elsevier, vol. 184(2), pages 814-815, January.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Entani, Tomoe & Maeda, Yutaka & Tanaka, Hideo, 2002. "Dual models of interval DEA and its extension to interval data," European Journal of Operational Research, Elsevier, vol. 136(1), pages 32-45, January.
    5. Zhu, Joe, 2003. "Efficiency evaluation with strong ordinal input and output measures," European Journal of Operational Research, Elsevier, vol. 146(3), pages 477-485, May.
    6. Timo Kuosmanen & Thierry Post, 2002. "Nonparametric Efficiency Analysis under Price Uncertainty: A First-Order Stochastic Dominance Approach," Journal of Productivity Analysis, Springer, vol. 17(3), pages 183-200, May.
    7. Zhu, Joe, 2003. "Imprecise data envelopment analysis (IDEA): A review and improvement with an application," European Journal of Operational Research, Elsevier, vol. 144(3), pages 513-529, February.
    8. Kuosmanen, Timo & Post, Thierry, 2001. "Measuring economic efficiency with incomplete price information: With an application to European commercial banks," European Journal of Operational Research, Elsevier, vol. 134(1), pages 43-58, October.
    9. Kuosmanen, Timo & Post, Thierry, 2003. "Measuring economic efficiency with incomplete price information," European Journal of Operational Research, Elsevier, vol. 144(2), pages 454-457, January.
    10. Camanho, A. S. & Dyson, R. G., 2005. "Cost efficiency measurement with price uncertainty: a DEA application to bank branch assessments," European Journal of Operational Research, Elsevier, vol. 161(2), pages 432-446, March.
    11. Kao, Chiang, 2006. "Interval efficiency measures in data envelopment analysis with imprecise data," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1087-1099, October.
    12. Despotis, Dimitris K. & Smirlis, Yiannis G., 2002. "Data envelopment analysis with imprecise data," European Journal of Operational Research, Elsevier, vol. 140(1), pages 24-36, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cui, Qiang & Lin, Jing-ling & Jin, Zi-yin, 2020. "Evaluating airline efficiency under “Carbon Neutral Growth from 2020” strategy through a Network Interval Slack-Based Measure," Energy, Elsevier, vol. 193(C).
    2. Blancard, Stéphane & Martin, Elsa, 2014. "Energy efficiency measurement in agriculture with imprecise energy content information," Energy Policy, Elsevier, vol. 66(C), pages 198-208.
    3. Fang, Lei & Li, Hecheng, 2012. "A comment on “cost efficiency in data envelopment analysis with data uncertainty”," European Journal of Operational Research, Elsevier, vol. 220(2), pages 588-590.
    4. Sahoo, Biresh K. & Mehdiloozad, Mahmood & Tone, Kaoru, 2014. "Cost, revenue and profit efficiency measurement in DEA: A directional distance function approach," European Journal of Operational Research, Elsevier, vol. 237(3), pages 921-931.
    5. Fang, Lei & Li, Hecheng, 2015. "Cost efficiency in data envelopment analysis under the law of one price," European Journal of Operational Research, Elsevier, vol. 240(2), pages 488-492.
    6. Lei Fang & Hecheng Li, 2013. "Lower bound of cost efficiency measure in DEA with incomplete price information," Journal of Productivity Analysis, Springer, vol. 40(2), pages 219-226, October.
    7. Amin Mostafaee & Milan Hladík, 2020. "Optimal value bounds in interval fractional linear programming and revenue efficiency measuring," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(3), pages 963-981, September.
    8. Hatami-Marbini, Adel & Arabmaldar, Aliasghar, 2021. "Robustness of Farrell cost efficiency measurement under data perturbations: Evidence from a US manufacturing application," European Journal of Operational Research, Elsevier, vol. 295(2), pages 604-620.
    9. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Toloo, Mehdi & Ghazizadeh, Mohammad Sadegh, 2016. "Eco-efficiency considering the issue of heterogeneity among power plants," Energy, Elsevier, vol. 111(C), pages 722-735.
    10. Wettemann, Patrick Johannes Christopher & Latacz-Lohmann, Uwe, 2017. "An efficiency-based concept to assess potential cost and greenhouse gas savings on German dairy farms," Agricultural Systems, Elsevier, vol. 152(C), pages 27-37.
    11. HATAMI-MARBINI, Adel & AGRELL, Per & AGHAYI, Nazila, 2013. "Imprecise data envelopment analysis for the two-stage process," LIDAM Discussion Papers CORE 2013004, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Dariush Akbarian, 2020. "Overall profit Malmquist productivity index under data uncertainty," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-20, December.
    13. Khosro Soleimani-Chamkhorami & Saeid Ghobadi, 2021. "Cost-efficiency under inter-temporal dependence," Annals of Operations Research, Springer, vol. 302(1), pages 289-312, July.
    14. Rashed Khanjani Shiraz & Adel Hatami-Marbini & Ali Emrouznejad & Hirofumi Fukuyama, 2020. "Chance-constrained cost efficiency in data envelopment analysis model with random inputs and outputs," Operational Research, Springer, vol. 20(3), pages 1863-1898, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rashed Khanjani Shiraz & Adel Hatami-Marbini & Ali Emrouznejad & Hirofumi Fukuyama, 2020. "Chance-constrained cost efficiency in data envelopment analysis model with random inputs and outputs," Operational Research, Springer, vol. 20(3), pages 1863-1898, September.
    2. Sahoo, Biresh K. & Mehdiloozad, Mahmood & Tone, Kaoru, 2014. "Cost, revenue and profit efficiency measurement in DEA: A directional distance function approach," European Journal of Operational Research, Elsevier, vol. 237(3), pages 921-931.
    3. HATAMI-MARBINI, Adel & AGRELL, Per & AGHAYI, Nazila, 2013. "Imprecise data envelopment analysis for the two-stage process," LIDAM Discussion Papers CORE 2013004, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Hatami-Marbini, Adel & Arabmaldar, Aliasghar, 2021. "Robustness of Farrell cost efficiency measurement under data perturbations: Evidence from a US manufacturing application," European Journal of Operational Research, Elsevier, vol. 295(2), pages 604-620.
    5. Fang, Lei & Li, Hecheng, 2012. "A comment on “cost efficiency in data envelopment analysis with data uncertainty”," European Journal of Operational Research, Elsevier, vol. 220(2), pages 588-590.
    6. Shabani, Amir & Visani, Franco & Barbieri, Paolo & Dullaert, Wout & Vigo, Daniele, 2019. "Reliable estimation of suppliers’ total cost of ownership: An imprecise data envelopment analysis model with common weights," Omega, Elsevier, vol. 87(C), pages 57-70.
    7. Park, K. Sam, 2010. "Duality, efficiency computations and interpretations in imprecise DEA," European Journal of Operational Research, Elsevier, vol. 200(1), pages 289-296, January.
    8. Yu Yu & Weiwei Zhu & Qian Zhang, 2019. "DEA cross-efficiency evaluation and ranking method based on interval data," Annals of Operations Research, Springer, vol. 278(1), pages 159-175, July.
    9. Cui, Qiang & Lin, Jing-ling & Jin, Zi-yin, 2020. "Evaluating airline efficiency under “Carbon Neutral Growth from 2020” strategy through a Network Interval Slack-Based Measure," Energy, Elsevier, vol. 193(C).
    10. Lei Fang & Hecheng Li, 2013. "Lower bound of cost efficiency measure in DEA with incomplete price information," Journal of Productivity Analysis, Springer, vol. 40(2), pages 219-226, October.
    11. Blancard, Stéphane & Martin, Elsa, 2014. "Energy efficiency measurement in agriculture with imprecise energy content information," Energy Policy, Elsevier, vol. 66(C), pages 198-208.
    12. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    13. Toloo, Mehdi & Mensah, Emmanuel Kwasi & Salahi, Maziar, 2022. "Robust optimization and its duality in data envelopment analysis," Omega, Elsevier, vol. 108(C).
    14. Quanling Wei & Tsung-Sheng Chang & Song Han, 2014. "Quantile–DEA classifiers with interval data," Annals of Operations Research, Springer, vol. 217(1), pages 535-563, June.
    15. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    16. Amin Mostafaee & Milan Hladík, 2020. "Optimal value bounds in interval fractional linear programming and revenue efficiency measuring," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(3), pages 963-981, September.
    17. Kao, Chiang, 2006. "Interval efficiency measures in data envelopment analysis with imprecise data," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1087-1099, October.
    18. Azadi, Majid & Farzipoor Saen, Reza, 2013. "A combination of QFD and imprecise DEA with enhanced Russell graph measure: A case study in healthcare," Socio-Economic Planning Sciences, Elsevier, vol. 47(4), pages 281-291.
    19. Fukuyama, Hirofumi & Shiraz, Rashed Khanjani, 2015. "Cost-effectiveness measures on convex and nonconvex technologies," European Journal of Operational Research, Elsevier, vol. 246(1), pages 307-319.
    20. Bohlool Ebrahimi & Madjid Tavana & Andreas Kleine & Andreas Dellnitz, 2021. "An epsilon-based data envelopment analysis approach for solving performance measurement problems with interval and ordinal dual-role factors," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(4), pages 1103-1124, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:202:y:2010:i:2:p:595-603. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.