IDEAS home Printed from https://ideas.repec.org/a/spr/snopef/v6y2025i3d10.1007_s43069-025-00506-0.html
   My bibliography  Save this article

The Efficiency Analysis and Ranking Employing Data Envelopment Analysis and Multi-Criteria Decision Analysis: Incorporating Cumulative Prospect Theory

Author

Listed:
  • Sweksha Srivastava

    (University School of Basic and Applied Sciences)

  • Abha Aggarwal

    (University School of Basic and Applied Sciences)

Abstract

This study proposes an integrated methodology for evaluating and ranking decision-making units (DMUs) characterized by multiple inputs and outputs by combining data envelopment analysis (DEA) and multi-criteria decision analysis (MCDA) with cumulative prospect theory (CPT), a behavioral decision-making framework. Recognizing that decision-making is often influenced by risk perception and behavioral biases, the proposed approach incorporates CPT to capture the psychological preferences of decision-makers under uncertainty by establishing prospect intervals for each input and output (or criterion) based on pessimistic and optimistic reference points. These prospect interval values are then aggregated and utilized for the efficiency evaluation and ranking of DMUs. Given that traditional DEA models frequently assign an efficiency score of one to several DMUs, posing challenges in their differentiation and ranking, the study introduces a hybrid approach that integrates DEA with the Measurement Alternatives and Ranking according to Compromise Solution (MARCOS) method. By benchmarking DMUs against ideal and anti-ideal solutions, MARCOS facilitates a more nuanced and comprehensive ranking process. The proposed framework is empirically validated using data from 30 assets listed in the Nifty 50 index, illustrating its effectiveness in providing a robust, behaviorally informed evaluation of DMUs. Additionally, a comparative analysis is conducted to assess the differences between the rankings generated by the two MCDA methods.

Suggested Citation

  • Sweksha Srivastava & Abha Aggarwal, 2025. "The Efficiency Analysis and Ranking Employing Data Envelopment Analysis and Multi-Criteria Decision Analysis: Incorporating Cumulative Prospect Theory," SN Operations Research Forum, Springer, vol. 6(3), pages 1-34, September.
  • Handle: RePEc:spr:snopef:v:6:y:2025:i:3:d:10.1007_s43069-025-00506-0
    DOI: 10.1007/s43069-025-00506-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43069-025-00506-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s43069-025-00506-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Somayeh Khezri & Gholam Reza Jahanshahloo & Akram Dehnokhalaji & Farhad Hosseinzadeh Lotfi, 2022. "A complete ranking of decision making units with interval data," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 43(3), pages 332-359.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. Hatefi, S.M. & Torabi, S.A., 2010. "A common weight MCDA-DEA approach to construct composite indicators," Ecological Economics, Elsevier, vol. 70(1), pages 114-120, November.
    4. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    5. F. Hosseinzadeh Lotfi & G. R. Jahanshahloo & M. Khodabakhshi & M. Rostamy-Malkhlifeh & Z. Moghaddas & M. Vaez-Ghasemi, 2013. "A Review of Ranking Models in Data Envelopment Analysis," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-20, July.
    6. Haoran Zhao & Sen Guo & Huiru Zhao, 2018. "Selecting the Optimal Micro-Grid Planning Program Using a Novel Multi-Criteria Decision Making Model Based on Grey Cumulative Prospect Theory," Energies, MDPI, vol. 11(7), pages 1-24, July.
    7. 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.
    8. Željko Stević & Nikola Brković, 2020. "A Novel Integrated FUCOM-MARCOS Model for Evaluation of Human Resources in a Transport Company," Logistics, MDPI, vol. 4(1), pages 1-14, February.
    9. Akram Dehnokhalaji & Behjat Hallaji & Narges Soltani & Jafar Sadeghi, 2017. "Convex cone-based ranking of decision-making units in DEA," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 861-880, July.
    10. Xing Shao & Meiqiang Wang, 2022. "Two-stage cross-efficiency evaluation based on prospect theory," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(7), pages 1620-1632, July.
    11. Siwei Xiao & Marios Dominikos Kremantzis & Leonidas Sotirios Kyrgiakos & George Vlontzos & Panos M. Pardalos, 2024. "Embracing fairness within a cross-efficiency hierarchical network DEA system," Operational Research, Springer, vol. 24(1), pages 1-31, March.
    12. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    13. Wu, Yunna & Xu, Chuanbo & Zhang, Ting, 2018. "Evaluation of renewable power sources using a fuzzy MCDM based on cumulative prospect theory: A case in China," Energy, Elsevier, vol. 147(C), pages 1227-1239.
    14. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    15. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    16. Cheng, Gang & Zervopoulos, Panagiotis & Qian, Zhenhua, 2013. "A variant of radial measure capable of dealing with negative inputs and outputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 225(1), pages 100-105.
    17. Madlener, Reinhard & Antunes, Carlos Henggeler & Dias, Luis C., 2009. "Assessing the performance of biogas plants with multi-criteria and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1084-1094, September.
    18. Mehdi Soltanifar & Hamid Sharafi, 2022. "A modified DEA cross efficiency method with negative data and its application in supplier selection," Journal of Combinatorial Optimization, Springer, vol. 43(1), pages 265-296, January.
    19. F. Hosseinzadeh Lotfi & G. R. Jahanshahloo & M. Khodabakhshi & M. Rostamy-Malkhlifeh & Z. Moghaddas & M. Vaez-Ghasemi, 2013. "A Review of Ranking Models in Data Envelopment Analysis," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    20. B. Senthil Arasu & Desti Kannaiah & Nancy Christina J. & Malik Shahzad Shabbir, 2021. "Selection of Variables in Data Envelopment Analysis for Evaluation of Stock Performance," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 46(3), pages 337-353, August.
    21. Emrouznejad, Ali & Anouze, Abdel Latef & Thanassoulis, Emmanuel, 2010. "A semi-oriented radial measure for measuring the efficiency of decision making units with negative data, using DEA," European Journal of Operational Research, Elsevier, vol. 200(1), pages 297-304, January.
    22. Miomir Stanković & Željko Stević & Dillip Kumar Das & Marko Subotić & Dragan Pamučar, 2020. "A New Fuzzy MARCOS Method for Road Traffic Risk Analysis," Mathematics, MDPI, vol. 8(3), pages 1-18, March.
    23. Sungmook Lim & Joe Zhu, 2015. "DEA cross-efficiency evaluation under variable returns to scale," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(3), pages 476-487, March.
    24. Patchara Phochanikorn & Chunqiao Tan, 2019. "An Integrated Multi-Criteria Decision-Making Model Based on Prospect Theory for Green Supplier Selection under Uncertain Environment: A Case Study of the Thailand Palm Oil Products Industry," Sustainability, MDPI, vol. 11(7), pages 1-22, March.
    25. Liang, Liang & Wu, Jie & Cook, Wade D. & Zhu, Joe, 2008. "Alternative secondary goals in DEA cross-efficiency evaluation," International Journal of Production Economics, Elsevier, vol. 113(2), pages 1025-1030, June.
    26. 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.
    27. Ruiyue Lin, 2020. "Cross-efficiency evaluation capable of dealing with negative data: A directional distance function based approach," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(3), pages 505-516, March.
    28. J A Sharp & W Meng & W Liu, 2007. "A modified slacks-based measure model for data envelopment analysis with ‘natural’ negative outputs and inputs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1672-1677, December.
    29. Kao, Chiang & Liu, Shiang-Tai, 2020. "A slacks-based measure model for calculating cross efficiency in data envelopment analysis," Omega, Elsevier, vol. 95(C).
    30. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    31. Sweksha Srivastava & Abha Aggarwal & Pooja Bansal, 2024. "Efficiency Evaluation of Assets and Optimal Portfolio Generation by Cross Efficiency and Cumulative Prospect Theory," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 129-158, January.
    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. Rezaeiani, M.J. & Foroughi, A.A., 2018. "Ranking efficient decision making units in data envelopment analysis based on reference frontier share," European Journal of Operational Research, Elsevier, vol. 264(2), pages 665-674.
    2. Lin, Shuguang & Shi, Hai-Liu & Wang, Ying-Ming, 2022. "An integrated slacks-based super-efficiency measure in the presence of nonpositive data," Omega, Elsevier, vol. 111(C).
    3. Amineh Ghazi & Farhad Hosseinzadeh Lotfi & Masoud Sanei, 2020. "Hybrid efficiency measurement and target setting based on identifying defining hyperplanes of the PPS with negative data," Operational Research, Springer, vol. 20(2), pages 1055-1092, June.
    4. Cova-Alonso, David José & Díaz-Hernández, Juan José & Martínez-Budría, Eduardo, 2021. "A strong efficiency measure for CCR/BCC models," European Journal of Operational Research, Elsevier, vol. 291(1), pages 284-295.
    5. Feng Li & Han Wu & Qingyuan Zhu & Liang Liang & Gang Kou, 2021. "Data envelopment analysis cross efficiency evaluation with reciprocal behaviors," Annals of Operations Research, Springer, vol. 302(1), pages 173-210, July.
    6. Sweksha Srivastava & Abha Aggarwal & Pooja Bansal, 2024. "Efficiency Evaluation of Assets and Optimal Portfolio Generation by Cross Efficiency and Cumulative Prospect Theory," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 129-158, January.
    7. Yung-ho Chiu & Chin-wei Huang & Chung-te Ting, 2012. "A non-radial measure of different systems for Taiwanese tourist hotels’ efficiency assessment," 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. 20(1), pages 45-63, March.
    8. Lin, Ruiyue & Liu, Yue, 2019. "Super-efficiency based on the directional distance function in the presence of negative data," Omega, Elsevier, vol. 85(C), pages 26-34.
    9. Ebrahimi, Bohlool & Dhamotharan, Lalitha & Ghasemi, Mohammad Reza & Charles, Vincent, 2022. "A cross-inefficiency approach based on the deviation variables framework," Omega, Elsevier, vol. 111(C).
    10. Mushtaq Taleb & Ruzelan Khalid & Ali Emrouznejad & Razamin Ramli, 2023. "Environmental efficiency under weak disposability: an improved super efficiency data envelopment analysis model with application for assessment of port operations considering NetZero," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6627-6656, July.
    11. Marcel Clermont & Julia Schaefer, 2019. "Identification of Outliers in Data Envelopment Analysis," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 71(4), pages 475-496, October.
    12. Josef Jablonský, 2025. "Analysis of citation impact of ORMS journals by DEA models," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(1), pages 343-365, January.
    13. Kao, Chiang, 2022. "Measuring efficiency in a general production possibility set allowing for negative data: An extension and a focus on returns to scale," European Journal of Operational Research, Elsevier, vol. 296(1), pages 267-276.
    14. Mohammad Izadikhah & Reza Farzipoor Saen & Razieh Roostaee, 2018. "How to assess sustainability of suppliers in the presence of volume discount and negative data in data envelopment analysis?," Annals of Operations Research, Springer, vol. 269(1), pages 241-267, October.
    15. Cui, Yuan & Pan, Hao & Huang, Yi-Di & Yang, Guo-liang, 2024. "How can sociological theories provide legitimacy to eco-efficiency evaluations? Embark on a journey toward understanding," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    16. Dongwei Yang & Qiong Xia, 2018. "Behavioral DEA model in evaluating the regional carrying states in China," Annals of Operations Research, Springer, vol. 268(1), pages 315-331, September.
    17. Svetlana Ratner & Andrey Lychev & Aleksei Rozhnov & Igor Lobanov, 2021. "Efficiency Evaluation of Regional Environmental Management Systems in Russia Using Data Envelopment Analysis," Mathematics, MDPI, vol. 9(18), pages 1-21, September.
    18. Rafael Benítez & Vicente Coll-Serrano & Vicente J. Bolós, 2021. "deaR-Shiny: An Interactive Web App for Data Envelopment Analysis," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    19. Enzo Barberio Mariano & Diogo Ferraz & Simone Cristina Oliveira Gobbo, 2021. "The Human Development Index with Multiple Data Envelopment Analysis Approaches: A Comparative Evaluation Using Social Network Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(2), pages 443-500, September.
    20. Mohammad Tavassoli & Mahsa Ghandehari & Masoud Taherinia, 2023. "Rang-adjusted measure: modelling and computational aspects from internal and external perspectives for network DEA," Operational Research, Springer, vol. 23(4), pages 1-34, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:spr:snopef:v:6:y:2025:i:3:d:10.1007_s43069-025-00506-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.