IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i6p1402-d1097290.html
   My bibliography  Save this article

Development of Bi-Objective Fuzzy Data Envelopment Analysis Model to Measure the Efficiencies of Decision-Making Units

Author

Listed:
  • Awadh Pratap Singh

    (School of Liberal Studies, University of Petroleum and Energy Studies, Prem Nagar 248007, Uttarakhand, India
    These authors contributed equally to this work.)

  • Musrrat Ali

    (Department of Basic Sciences, PYD, King Faisal University, Al Ahsa 31982, Saudi Arabia
    These authors contributed equally to this work.)

Abstract

The proposed bi-objective fuzzy data envelopment analysis (BOFDEA) model is a new approach to assess the performance efficiency of decision-making units (DMUs) in uncertain environments using α -cuts. The model is based on fuzzy data envelopment analysis (FDEA) and considers two objectives, and a solution method and ranking system are provided. Generally, the efficiency score obtained for a DMU using the α -cut approach is an interval. Intervals are partially ordered sets, due to which ranking intervals is a challenging task. The proposed BOFDEA model with α -cuts provides the efficiency of DMUs in the crisp form, not in the form of intervals. Due to this, ranking DMUs with the proposed method’s help becomes very easy and less computationally. The proposed model has been validated through numerical examples, and a real-world application in the education sector has been shown to demonstrate its practicality.

Suggested Citation

  • Awadh Pratap Singh & Musrrat Ali, 2023. "Development of Bi-Objective Fuzzy Data Envelopment Analysis Model to Measure the Efficiencies of Decision-Making Units," Mathematics, MDPI, vol. 11(6), pages 1-15, March.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:6:p:1402-:d:1097290
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/6/1402/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/11/6/1402/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jolly Puri & Shiv Prasad Yadav, 2013. "Performance evaluation of public and private sector banks in India using DEA approach," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 18(1), pages 91-121.
    2. Adel Hatami-Marbini & Madjid Tavana & Alireza Ebrahimi, 2011. "A fully fuzzified data envelopment analysis model," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 3(3), pages 252-264.
    3. Y M Wang & K S Chin & J B Yang, 2007. "Measuring the performances of decision-making units using geometric average efficiency," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(7), pages 929-937, July.
    4. 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.
    5. Sandeep Kumar Mogha & Shiv Prasad Yadav & S.P. Singh, 2016. "Estimating technical efficiency of public sector hospitals of Uttarakhand (India)," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 25(3), pages 371-399.
    6. Tyagi, Preeti & Yadav, Shiv Prasad & Singh, S.P., 2009. "Relative performance of academic departments using DEA with sensitivity analysis," Evaluation and Program Planning, Elsevier, vol. 32(2), pages 168-177, May.
    7. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    8. Awadh Pratap Singh & Shiv Prasad Yadav & Preeti Tyagi, 2022. "Performance assessment of higher educational institutions in India using data envelopment analysis and re-evaluation of NIRF Rankings," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(2), pages 1024-1035, April.
    9. 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)

    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. Meena Yadav & Shiv Prasad Yadav, 2022. "Performance efficiency measurement of MGNREGA 2018-19 in Indian States and Union Territories based on DEA," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(4), pages 1714-1721, August.
    2. Aghayi, Nazila & Maleki, Bentolhoda, 2016. "Efficiency measurement of DMUs with undesirable outputs under uncertainty based on the directional distance function: Application on bank industry," Energy, Elsevier, vol. 112(C), pages 376-387.
    3. Awadh Pratap Singh & Shiv Prasad Yadav & Preeti Tyagi, 2022. "Performance assessment of higher educational institutions in India using data envelopment analysis and re-evaluation of NIRF Rankings," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(2), pages 1024-1035, April.
    4. Liu, C.H. & Lin, Sue J. & Lewis, Charles, 2010. "Evaluation of thermal power plant operational performance in Taiwan by data envelopment analysis," Energy Policy, Elsevier, vol. 38(2), pages 1049-1058, February.
    5. Wai‐Peng Wong & Qiang Deng & Ming-Lang Tseng & Loo‐Hay Lee & Chee‐Wooi Hooy, 2014. "A Stochastic Setting To Bank Financial Performance For Refining Efficiency Estimates," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(4), pages 225-245, October.
    6. Jarmila Horváthová & Martina Mokrišová & Martin Bača, 2023. "Bankruptcy Prediction for Sustainability of Businesses: The Application of Graph Theoretical Modeling," Mathematics, MDPI, vol. 11(24), pages 1-20, December.
    7. Cristian Barra & Roberto Zotti, 2016. "Measuring Efficiency in Higher Education: An Empirical Study Using a Bootstrapped Data Envelopment Analysis," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(1), pages 11-33, February.
    8. Wang, Ying-Ming & Lan, Yi-Xin, 2013. "Estimating most productive scale size with double frontiers data envelopment analysis," Economic Modelling, Elsevier, vol. 33(C), pages 182-186.
    9. Shaher Z. Zahran & Jobair Bin Alam & Abdulrahem H. Al-Zahrani & Yiannis Smirlis & Stratos Papadimitriou & Vangelis Tsioumas, 2020. "Analysis of port efficiency using imprecise and incomplete data," Operational Research, Springer, vol. 20(1), pages 219-246, March.
    10. Tavares, Rafael Santos & Angulo-Meza, Lidia & Sant'Anna, Annibal Parracho, 2021. "A proposed multistage evaluation approach for Higher Education Institutions based on network Data envelopment analysis: A Brazilian experience," Evaluation and Program Planning, Elsevier, vol. 89(C).
    11. Róbert Štefko & Jarmila Horváthová & Martina Mokrišová, 2020. "Bankruptcy Prediction with the Use of Data Envelopment Analysis: An Empirical Study of Slovak Businesses," JRFM, MDPI, vol. 13(9), pages 1-15, September.
    12. Amara, Nabil & Rhaiem, Mehdi & Halilem, Norrin, 2020. "Assessing the research efficiency of Canadian scholars in the management field: Evidence from the DEA and fsQCA," Journal of Business Research, Elsevier, vol. 115(C), pages 296-306.
    13. Kao, Chiang & Liu, Shiang-Tai, 2009. "Stochastic data envelopment analysis in measuring the efficiency of Taiwan commercial banks," European Journal of Operational Research, Elsevier, vol. 196(1), pages 312-322, July.
    14. Majid Baghery & Samuel Yousefi & Mustafa Jahangoshai Rezaee, 2018. "Risk measurement and prioritization of auto parts manufacturing processes based on process failure analysis, interval data envelopment analysis and grey relational analysis," Journal of Intelligent Manufacturing, Springer, vol. 29(8), pages 1803-1825, December.
    15. Masahiro Inuiguchi & Fumiki Mizoshita, 2012. "Qualitative and quantitative data envelopment analysis with interval data," Annals of Operations Research, Springer, vol. 195(1), pages 189-220, May.
    16. Kao, Chiang & Lin, Pei-Huang, 2011. "Qualitative factors in data envelopment analysis: A fuzzy number approach," European Journal of Operational Research, Elsevier, vol. 211(3), pages 586-593, June.
    17. Jolly Puri & Shiv Prasad Yadav, 2017. "Improved DEA models in the presence of undesirable outputs and imprecise data: an application to banking industry in India," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1608-1629, November.
    18. Jolly Puri & Shiv Prasad Yadav & Harish Garg, 2017. "A new multi-component DEA approach using common set of weights methodology and imprecise data: an application to public sector banks in India with undesirable and shared resources," Annals of Operations Research, Springer, vol. 259(1), pages 351-388, December.
    19. Toloo, Mehdi & Mensah, Emmanuel Kwasi & Salahi, Maziar, 2022. "Robust optimization and its duality in data envelopment analysis," Omega, Elsevier, vol. 108(C).
    20. Jianhui Xie & Qiwei Xie & Yongjun Li & Liang Liang, 2021. "Solving data envelopment analysis models with sum-of-fractional objectives: a global optimal approach based on the multiparametric disaggregation technique," Annals of Operations Research, Springer, vol. 304(1), pages 453-480, September.

    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:gam:jmathe:v:11:y:2023:i:6:p:1402-:d:1097290. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.