IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i4p529-d1335815.html
   My bibliography  Save this article

A Bilevel DEA Model for Efficiency Evaluation and Target Setting with Stochastic Conditions

Author

Listed:
  • Andreas C. Georgiou

    (Quantitative Methods and Decision Analysis Lab, Department of Business Administration, University of Macedonia, GR-54636 Thessaloniki, Greece)

  • Konstantinos Kaparis

    (Quantitative Methods and Decision Analysis Lab, Department of Business Administration, University of Macedonia, GR-54636 Thessaloniki, Greece)

  • Eleni-Maria Vretta

    (Quantitative Methods and Decision Analysis Lab, Department of Business Administration, University of Macedonia, GR-54636 Thessaloniki, Greece)

  • Kyriakos Bitsis

    (Quantitative Methods and Decision Analysis Lab, Department of Business Administration, University of Macedonia, GR-54636 Thessaloniki, Greece)

  • George Paltayian

    (Quantitative Methods and Decision Analysis Lab, Department of Business Administration, University of Macedonia, GR-54636 Thessaloniki, Greece)

Abstract

The effective allocation of limited resources and the establishment of targeted goals play a pivotal role in enhancing the overall efficiency of large enterprises and organizations. To achieve optimal organizational efficiency, managers seek dynamic strategies that adapt to the constraints of limited and uncertain historical data. This paper introduces an evaluation of organizational efficiency through a stochastic framework, employing a bilevel data envelopment analysis (DEA) approach. This decision-making process is centralized within a decision-making unit (DMU) overseeing subordinate decision-making units (subDMUs). Discrete scenarios, each associated with a realization probability, define the uncertain parameters in the bilevel DEA-based model. This stochastic approach allows for recourse actions upon scenario realization leading to an enhanced overall organizational strategy. Decision-makers acting within uncertain and dynamic environments can benefit from this research since it allows the investigation of efficiency assessment under alternative scenarios in the presence of volatility and risk. The potential impact of applying this methodology varies depending on the specific domain. Although, the context of this paper focuses on banking, in general, enhancing resource allocation and target setting under stochasticity, contributes to advancing sustainability across all its three dimensions (economic, environmental, social). As mentioned earlier, the practical application of our approach is demonstrated via a case study in the banking sector.

Suggested Citation

  • Andreas C. Georgiou & Konstantinos Kaparis & Eleni-Maria Vretta & Kyriakos Bitsis & George Paltayian, 2024. "A Bilevel DEA Model for Efficiency Evaluation and Target Setting with Stochastic Conditions," Mathematics, MDPI, vol. 12(4), pages 1-21, February.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:4:p:529-:d:1335815
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/4/529/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/12/4/529/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wu, Jie & Zhu, Qingyuan & Ji, Xiang & Chu, Junfei & Liang, Liang, 2016. "Two-stage network processes with shared resources and resources recovered from undesirable outputs," European Journal of Operational Research, Elsevier, vol. 251(1), pages 182-197.
    2. Yu, Ming-Miin & Chern, Ching-Chin & Hsiao, Bo, 2013. "Human resource rightsizing using centralized data envelopment analysis: Evidence from Taiwan's Airports," Omega, Elsevier, vol. 41(1), pages 119-130.
    3. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    4. Sebastián Lozano & Gabriel Villa, 2004. "Centralized Resource Allocation Using Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 22(1), pages 143-161, July.
    5. Afsharian, Mohsen & Ahn, Heinz & Thanassoulis, Emmanuel, 2019. "A frontier-based system of incentives for units in organisations with varying degrees of decentralisation," European Journal of Operational Research, Elsevier, vol. 275(1), pages 224-237.
    6. Lawrence M. Seiford & Joe Zhu, 1999. "Profitability and Marketability of the Top 55 U.S. Commercial Banks," Management Science, INFORMS, vol. 45(9), pages 1270-1288, September.
    7. Wang, Ke & Huang, Wei & Wu, Jie & Liu, Ying-Nan, 2014. "Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA," Omega, Elsevier, vol. 44(C), pages 5-20.
    8. Afsharian, Mohsen & Ahn, Heinz & Thanassoulis, Emmanuel, 2017. "A DEA-based incentives system for centrally managed multi-unit organisations," European Journal of Operational Research, Elsevier, vol. 259(2), pages 587-598.
    9. Fang, Lei, 2013. "A generalized DEA model for centralized resource allocation," European Journal of Operational Research, Elsevier, vol. 228(2), pages 405-412.
    10. Beasley, J. E., 2003. "Allocating fixed costs and resources via data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 147(1), pages 198-216, May.
    11. Portela, Maria Conceicao A. Silva & Thanassoulis, Emmanuel, 2007. "Comparative efficiency analysis of Portuguese bank branches," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1275-1288, March.
    12. Chen, Yao & Du, Juan & David Sherman, H. & Zhu, Joe, 2010. "DEA model with shared resources and efficiency decomposition," European Journal of Operational Research, Elsevier, vol. 207(1), pages 339-349, November.
    13. Zha, Yong & Liang, Liang, 2010. "Two-stage cooperation model with input freely distributed among the stages," European Journal of Operational Research, Elsevier, vol. 205(2), pages 332-338, September.
    14. Chiang Kao, 2014. "Efficiency Decomposition in Network Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 55-77, Springer.
    15. Athanassopoulos, Antreas D., 1995. "Goal programming & data envelopment analysis (GoDEA) for target-based multi-level planning: Allocating central grants to the Greek local authorities," European Journal of Operational Research, Elsevier, vol. 87(3), pages 535-550, December.
    16. Fukuyama, Hirofumi & Matousek, Roman, 2011. "Efficiency of Turkish banking: Two-stage network system. Variable returns to scale model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 75-91, February.
    17. Qiu, Qingan & Cui, Lirong & Gao, Hongda & Yi, He, 2018. "Optimal allocation of units in sequential probability series systems," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 351-363.
    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. Ang, Sheng & Liu, Pei & Yang, Feng, 2020. "Intra-Organizational and inter-organizational resource allocation in two-stage network systems," Omega, Elsevier, vol. 91(C).
    2. Amirteimoori, Alireza & Kazemi Matin, Reza & Yadollahi, Amir Hossein, 2024. "Stochastic resource reallocation in two-stage production processes with undesirable outputs: An empirical study on the power industry," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    3. Lozano, Sebastián, 2016. "Slacks-based inefficiency approach for general networks with bad outputs: An application to the banking sector," Omega, Elsevier, vol. 60(C), pages 73-84.
    4. Fukuyama, Hirofumi & Matousek, Roman & Tzeremes, Nickolaos G., 2020. "A Nerlovian cost inefficiency two-stage DEA model for modeling banks’ production process: Evidence from the Turkish banking system," Omega, Elsevier, vol. 95(C).
    5. Chen, Ya & Li, Yongjun & Liang, Liang & Salo, Ahti & Wu, Huaqing, 2016. "Frontier projection and efficiency decomposition in two-stage processes with slacks-based measures," European Journal of Operational Research, Elsevier, vol. 250(2), pages 543-554.
    6. Lim, Dong-Joon & Kim, Moon-Su, 2022. "Measuring dynamic efficiency with variable time lag effects," Omega, Elsevier, vol. 108(C).
    7. Afsharian, Mohsen & Ahn, Heinz & Harms, Sören Guntram, 2021. "A review of DEA approaches applying a common set of weights: The perspective of centralized management," European Journal of Operational Research, Elsevier, vol. 294(1), pages 3-15.
    8. Kourtzidis, Stavros & Matousek, Roman & Tzeremes, Nickolaos G., 2021. "Modelling a multi-period production process: Evidence from the Japanese regional banks," European Journal of Operational Research, Elsevier, vol. 294(1), pages 327-339.
    9. Li, Feng & Zhu, Qingyuan & Chen, Zhi, 2019. "Allocating a fixed cost across the decision making units with two-stage network structures," Omega, Elsevier, vol. 83(C), pages 139-154.
    10. Panagiotis Mitropoulos & Ioannis Mitropoulos, 2020. "Performance evaluation of retail banking services: Is there a trade‐off between production and quality?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(7), pages 1237-1250, October.
    11. Tatiana Bencova & Andrea Bohacikova, 2022. "DEA in Performance Measurement of Two-Stage Processes: Comparative Overview of the Literature," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 111-129.
    12. Menghan Chen & Sheng Ang & Lijing Jiang & Feng Yang, 2020. "Centralized resource allocation based on cross-evaluation considering organizational objective and individual preferences," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(2), pages 529-565, June.
    13. Wu, Huaqing & Lv, Kui & Liang, Liang & Hu, Hanhui, 2017. "Measuring performance of sustainable manufacturing with recyclable wastes: A case from China’s iron and steel industry," Omega, Elsevier, vol. 66(PA), pages 38-47.
    14. Arocena, Pablo & Cabasés, Fermín & Pascual, Pedro, 2022. "A centralized directional distance model for efficient and horizontally equitable grants allocation to local governments," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    15. Wu, Jie & Zhu, Qingyuan & Ji, Xiang & Chu, Junfei & Liang, Liang, 2016. "Two-stage network processes with shared resources and resources recovered from undesirable outputs," European Journal of Operational Research, Elsevier, vol. 251(1), pages 182-197.
    16. Lorenzo Castelli & Raffaele Pesenti & Walter Ukovich, 2010. "A classification of DEA models when the internal structure of the Decision Making Units is considered," Annals of Operations Research, Springer, vol. 173(1), pages 207-235, January.
    17. AGRELL, Per & HATAMI-MARBINI, Adel, 2011. "Frontier-based performance analysis models for supply chain management; state of the art and research directions," LIDAM Discussion Papers CORE 2011069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Ane Elixabete Ripoll-Zarraga & Sebastián Lozano, 2020. "A centralised DEA approach to resource reallocation in Spanish airports," Annals of Operations Research, Springer, vol. 288(2), pages 701-732, May.
    19. Xiong, Xi & Yang, Guo-liang & Zhou, De-qun & Wang, Zi-long, 2022. "How to allocate multi-period research resources? Centralized resource allocation for public universities in China using a parallel DEA-based approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    20. Weiwei Zhu & Qian Zhang & Haiqing Wang, 2019. "Fixed costs and shared resources allocation in two-stage network DEA," Annals of Operations Research, Springer, vol. 278(1), pages 177-194, July.

    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:12:y:2024:i:4:p:529-:d:1335815. 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.