IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v26y2021i3p4127-4136.html
   My bibliography  Save this article

Restricting the relative weights in data envelopment analysis

Author

Listed:
  • Hosein Arman
  • Abdollah Hadi‐Vencheh

Abstract

In this paper, we address the problem of relative weight restriction in data envelopment analysis (DEA). A fuzzy‐based approach to restricting the relative weights is proposed in this study. Unlike the classical weight restriction methods, the proposed approach has an interactive orientation. That is, similar to analytical hierarchy process, the proposed method shares the decision maker (DM) in weight restriction process. Here, the preferences of DM are asked via pairwise comparison matrices. Then, the weights of factors (inputs/outputs) are extracted from these matrices. These weights, finally, are incorporated in multiplier DEA models as the parametric triangular fuzzy numbers, in which, the parameter value indicates the degree of conformity of the relative weights according to DM views. To best of our knowledge, no one has been yet utilized fuzzy set theory to control the relative weights in DEA. Putting in another word, the contribution of this study is that the authors propose a new approach based on fuzzy set theory to weight restriction in DEA. A last, a real case on financial banking efficiency is used to illustrate the proposed approach.

Suggested Citation

  • Hosein Arman & Abdollah Hadi‐Vencheh, 2021. "Restricting the relative weights in data envelopment analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4127-4136, July.
    • Handle: RePEc:wly:ijfiec:v:26:y:2021:i:3:p:4127-4136
    DOI: 10.1002/ijfe.2007
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.2007
    Download Restriction: no
    File URL: https://libkey.io/10.1002/ijfe.2007?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
    ---><---

    References listed on IDEAS

    as
    1. Dimitrov, Stanko & Sutton, Warren, 2013. "Generalized symmetric weight assignment technique: Incorporating managerial preferences in data envelopment analysis using a penalty function," Omega, Elsevier, vol. 41(1), pages 48-54.
    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. Sarrico, C. S. & Dyson, R. G., 2004. "Restricting virtual weights in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 159(1), pages 17-34, November.
    4. Podinovski, V.V., 2007. "Computation of efficient targets in DEA models with production trade-offs and weight restrictions," European Journal of Operational Research, Elsevier, vol. 181(2), pages 586-591, September.
    5. Halme, Merja & Korhonen, Pekka, 2000. "Restricting weights in value efficiency analysis," European Journal of Operational Research, Elsevier, vol. 126(1), pages 175-188, October.
    6. Podinovski, V. V., 1999. "Side effects of absolute weight bounds in DEA models," European Journal of Operational Research, Elsevier, vol. 115(3), pages 583-595, June.
    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. Roll, Y & Golany, B., 1993. "Alternate methods of treating factor weights in DEA," Omega, Elsevier, vol. 21(1), pages 99-109, January.
    9. Podinovski, V. V., 2004. "Suitability and redundancy of non-homogeneous weight restrictions for measuring the relative efficiency in DEA," European Journal of Operational Research, Elsevier, vol. 154(2), pages 380-395, April.
    10. Podinovski, Victor V. & Bouzdine-Chameeva, Tatiana, 2015. "Consistent weight restrictions in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 244(1), pages 201-209.
    11. Thompson, Russell G. & Langemeier, Larry N. & Lee, Chih-Tah & Lee, Euntaik & Thrall, Robert M., 1990. "The role of multiplier bounds in efficiency analysis with application to Kansas farming," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 93-108.
    12. Estellita Lins, M.P. & Moreira da Silva, A.C. & Lovell, C.A.K., 2007. "Avoiding infeasibility in DEA models with weight restrictions," European Journal of Operational Research, Elsevier, vol. 181(2), pages 956-966, September.
    13. Dimitrov, Stanko & Sutton, Warren, 2010. "Promoting symmetric weight selection in data envelopment analysis: A penalty function approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 281-288, January.
    14. Ennen, David & Batool, Irem, 2018. "Airport efficiency in Pakistan - A Data Envelopment Analysis with weight restrictions," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 205-212.
    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. Ströhl, Florian & Borsch, Erik & Souren, Rainer, 2018. "Integration von Gewichtsrestriktionen in das DEA-Modell nach Charnes, Cooper und Rhodes: Exemplarische Optionen und Auswirkungen," Ilmenauer Schriften zur Betriebswirtschaftslehre, Technische Universität Ilmenau, Institut für Betriebswirtschaftslehre, volume 3, number 32018, September.
    2. Podinovski, Victor V., 2016. "Optimal weights in DEA models with weight restrictions," European Journal of Operational Research, Elsevier, vol. 254(3), pages 916-924.
    3. Dimitrov, Stanko & Sutton, Warren, 2010. "Promoting symmetric weight selection in data envelopment analysis: A penalty function approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 281-288, January.
    4. Roets, Bart & Verschelde, Marijn & Christiaens, Johan, 2018. "Multi-output efficiency and operational safety: An analysis of railway traffic control centre performance," European Journal of Operational Research, Elsevier, vol. 271(1), pages 224-237.
    5. C Kao & H-T Hung, 2005. "Data envelopment analysis with common weights: the compromise solution approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(10), pages 1196-1203, October.
    6. Ramón, Nuria & Ruiz, José L. & Sirvent, Inmaculada, 2010. "A multiplier bound approach to assess relative efficiency in DEA without slacks," European Journal of Operational Research, Elsevier, vol. 203(1), pages 261-269, May.
    7. Podinovski, Victor V. & Bouzdine-Chameeva, Tatiana, 2016. "On single-stage DEA models with weight restrictions," European Journal of Operational Research, Elsevier, vol. 248(3), pages 1044-1050.
    8. Somayeh Razipour-GhalehJough & Farhad Hosseinzadeh Lotfi & Gholamreza Jahanshahloo & Mohsen Rostamy-malkhalifeh & Hamid Sharafi, 2020. "Finding closest target for bank branches in the presence of weight restrictions using data envelopment analysis," Annals of Operations Research, Springer, vol. 288(2), pages 755-787, May.
    9. Dimitrov, Stanko & Sutton, Warren, 2013. "Generalized symmetric weight assignment technique: Incorporating managerial preferences in data envelopment analysis using a penalty function," Omega, Elsevier, vol. 41(1), pages 48-54.
    10. Victor V. Podinovski & Wan Rohaida Wan Husain, 2017. "The hybrid returns-to-scale model and its extension by production trade-offs: an application to the efficiency assessment of public universities in Malaysia," Annals of Operations Research, Springer, vol. 250(1), pages 65-84, March.
    11. Pereira, Miguel Alves & Camanho, Ana Santos & Figueira, José Rui & Marques, Rui Cunha, 2021. "Incorporating preference information in a range directional composite indicator: The case of Portuguese public hospitals," European Journal of Operational Research, Elsevier, vol. 294(2), pages 633-650.
    12. Tavana, Madjid & Ebrahimnejad, Ali & Santos-Arteaga, Francisco J. & Mansourzadeh, Seyed Mehdi & Matin, Reza Kazemi, 2018. "A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 70-89.
    13. Ghasemi, M.-R. & Ignatius, Joshua & Emrouznejad, Ali, 2014. "A bi-objective weighted model for improving the discrimination power in MCDEA," European Journal of Operational Research, Elsevier, vol. 233(3), pages 640-650.
    14. Dimitrov Stanko, 2014. "Comparing Data Envelopment Analysis and Human Decision Making Unit Rankings: A Survey Approach," Stochastics and Quality Control, De Gruyter, vol. 29(2), pages 129-141, December.
    15. Podinovski, V. V., 2004. "Suitability and redundancy of non-homogeneous weight restrictions for measuring the relative efficiency in DEA," European Journal of Operational Research, Elsevier, vol. 154(2), pages 380-395, April.
    16. See, Kok Fong & Ng, Ying Chu & Yu, Ming-Miin, 2022. "An alternative assessment approach to national higher education system evaluation," Evaluation and Program Planning, Elsevier, vol. 94(C).
    17. T Joro & E-J Viitala, 2004. "Weight-restricted DEA in action: from expert opinions to mathematical models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 814-821, August.
    18. Kalinichenko, Olena & Amado, Carla A.F. & Santos, Sérgio P., 2022. "Exploring the potential of Data Envelopment Analysis for enhancing pay-for-performance programme design in primary health care," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1084-1100.
    19. Victor V. Podinovski & Tatiana Bouzdine-Chameeva, 2013. "Weight Restrictions and Free Production in Data Envelopment Analysis," Operations Research, INFORMS, vol. 61(2), pages 426-437, April.
    20. Allen, R. & Thanassoulis, E., 2004. "Improving envelopment in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 363-379, April.

    More about this item

    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:wly:ijfiec:v:26:y:2021:i:3:p:4127-4136. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.