IDEAS home Printed from https://ideas.repec.org/a/spr/operea/v25y2025i1d10.1007_s12351-024-00890-1.html
   My bibliography  Save this article

Decisional performance efficiencies of cross-efficiency DEA decision-making units using benevolent criterion

Author

Listed:
  • Parag C. Pendharkar

    (Pennsylvania State University at Harrisburg)

Abstract

This paper uses the maximum decisional efficiency (MDE) principle to rank decisional performance efficiencies of cross-efficiency (CE) data envelopment analysis (DEA) decision-making units (DMUs) that use benevolent criterion. Under the benevolent criterion, each DMU independently selects a set of common weights to maximize the average peer efficiency scores. The performance of each DMU in selecting the set of common weights is called the decisional performance efficiency (DPE) of the DMU. The DPEs of all DMUs are assumed to be distributed as a monotone increasing probability density function (pdf) of unknown parameters. A maximum-likelihood (ML) approach using a genetic algorithm is used to learn the parameters of the pdf. Once the underlying parameters of the pdf are known, DPEs can be computed and the DMUs can be ranked based on their DPEs. Additionally, the Markov Chain Monte Carlo technique can be applied to establish confidence interval bounds on the ML parameter describing the MDE pdf. Three examples using datasets from the literature are provided.

Suggested Citation

  • Parag C. Pendharkar, 2025. "Decisional performance efficiencies of cross-efficiency DEA decision-making units using benevolent criterion," Operational Research, Springer, vol. 25(1), pages 1-29, March.
  • Handle: RePEc:spr:operea:v:25:y:2025:i:1:d:10.1007_s12351-024-00890-1
    DOI: 10.1007/s12351-024-00890-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12351-024-00890-1
    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/s12351-024-00890-1?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 search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Pendharkar, Parag C. & Koehler, Gary J., 2007. "A general steady state distribution based stopping criteria for finite length genetic algorithms," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1436-1451, February.
    3. Marvin D. Troutt, 1995. "A Maximum Decisional Efficiency Estimation Principle," Management Science, INFORMS, vol. 41(1), pages 76-82, January.
    4. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    5. Pendharkar, Parag C., 2006. "Scale economies and production function estimation for object-oriented software component and source code documentation size," European Journal of Operational Research, Elsevier, vol. 172(3), pages 1040-1050, August.
    6. M.D. Troutt, 1997. "Derivation of the Maximin Efficiency Ratio model from the maximum decisional efficiency principle," Annals of Operations Research, Springer, vol. 73(0), pages 323-338, October.
    7. Jin, Feifei & Cai, Yuhang & Zhou, Ligang & Ding, Tao, 2023. "Regret-rejoice two-stage multiplicative DEA models-driven cross-efficiency evaluation with probabilistic linguistic information," Omega, Elsevier, vol. 117(C).
    8. Pendharkar, Parag C., 2021. "Allocating fixed costs using multi-coalition epsilon equilibrium," International Journal of Production Economics, Elsevier, vol. 239(C).
    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. Kang, Hee Jay & Kim, Changhee & Choi, Kanghwa, 2024. "Combining bootstrap data envelopment analysis with social networks for rank discrimination and suitable potential benchmarks," European Journal of Operational Research, Elsevier, vol. 312(1), pages 283-297.
    2. 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.
    3. Alessandra Cepparulo & Gilles Mourre, 2020. "How and How Much? The Growth-Friendliness of Public Spending through the Lens," European Economy - Discussion Papers 132, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    4. Peyrache, Antonio & Rose, Christiern & Sicilia, Gabriela, 2020. "Variable selection in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 282(2), pages 644-659.
    5. Richard Simper & Maximilian J.B. Hall & Wenbin B. Liu & Valentin Zelenyuk & Zhongbao Zhou, 2014. "How Relevant is the Choice of Risk Management Control Variable to Non-parametric Bank Profit Efficiency Analysis?," CEPA Working Papers Series WP122014, School of Economics, University of Queensland, Australia.
    6. Ti-An Chen, 2022. "Business Performance Evaluation for Tourism Factory: Using DEA Approach and Delphi Method," Sustainability, MDPI, vol. 14(15), pages 1-19, July.
    7. Wijesiri, Mahinda & Yaron, Jacob & Meoli, Michele, 2017. "Assessing the financial and outreach efficiency of microfinance institutions: Do age and size matter?," Journal of Multinational Financial Management, Elsevier, vol. 40(C), pages 63-76.
    8. Khoshroo, Alireza & Izadikhah, Mohammad & Emrouznejad, Ali, 2022. "Total factor energy productivity considering undesirable pollutant outputs: A new double frontier based malmquist productivity index," Energy, Elsevier, vol. 258(C).
    9. Guilhermina Rego & Rui Nunes & José Costa, 2010. "The challenge of corporatisation: the experience of Portuguese public hospitals," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 11(4), pages 367-381, August.
    10. Wang, Chia-Nan & Nguyen, Xuan-Tho & Le, Thi-Dao & Hsueh, Ming-Hsien, 2018. "A partner selection approach for strategic alliance in the global aerospace and defense industry," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 190-204.
    11. Hsiao-Yen Mao & Wen-Min Lu & Hsin-Yen Shieh, 2023. "Exploring the Influence of Environmental Investment on Multinational Enterprises’ Performance from the Sustainability and Marketability Efficiency Perspectives," Sustainability, MDPI, vol. 15(10), pages 1-23, May.
    12. Wu, Jie & An, Qingxian & Xiong, Beibei & Chen, Ya, 2013. "Congestion measurement for regional industries in China: A data envelopment analysis approach with undesirable outputs," Energy Policy, Elsevier, vol. 57(C), pages 7-13.
    13. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    14. Ibrahim Alnafrah, 2021. "Efficiency evaluation of BRICS’s national innovation systems based on bias-corrected network data envelopment analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-28, December.
    15. Kim, Nam Hyok & He, Feng & Kwon, O Chol, 2023. "Combining common-weights DEA window with the Malmquist index: A case of China’s iron and steel industry," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    16. Esteve, Miriam & Aparicio, Juan & Rodriguez-Sala, Jesus J. & Zhu, Joe, 2023. "Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull," European Journal of Operational Research, Elsevier, vol. 304(2), pages 729-744.
    17. Perrigot, Rozenn & Barros, Carlos Pestana, 2008. "Technical efficiency of French retailers," Journal of Retailing and Consumer Services, Elsevier, vol. 15(4), pages 296-305.
    18. Wei-Kang Wang & Wen-Min Lu & Qian Long Kweh & Mohammad Nourani & Rong-Suei Hong, 2021. "Interlocking directorates and dynamic corporate performance: the roles of centrality, structural holes and number of connections in social networks," Review of Managerial Science, Springer, vol. 15(2), pages 437-457, February.
    19. Ji, Wei & Huang, Zhengfeng & Gao, Gao & Zheng, Pengjun, 2024. "Evaluation of integrated transport efficiency and equity at the county level——taking the counties in ningbo city as an example," Transport Policy, Elsevier, vol. 148(C), pages 257-272.
    20. Mohammad Nourani & Wen‐Min Lu & Irene Wei Kiong Ting, 2020. "Vicarious warfare and dynamic efficiency of companies in the aerospace and defence industry," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(4), pages 641-650, June.

    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:operea:v:25:y:2025:i:1:d:10.1007_s12351-024-00890-1. 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.