IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v57y2006i11d10.1057_palgrave.jors.2602117.html
   My bibliography  Save this article

Random effects logistic regression model for ranking efficiency in data envelopment analysis

Author

Listed:
  • S Y Sohn

    (Yonsei University)

Abstract

Ranking efficiency based on data envelopment analysis (DEA) results can be used for grouping decision-making units (DMUs). The resulting group membership can be partly related to the environmental characteristics of DMU, which are not used either as input or output. Utilizing the expert knowledge on super efficiency DEA results, we propose a multinomial Dirichlet regression model, which can be used for the purpose of selection of new projects. A case study is presented in the context of ranking analysis of new information technology commercialization projects. It is expected that our proposed approach can complement the DEA ranking results with environmental factors and at the same time it facilitates the prediction of efficiency of new DMUs with only given environmental characteristics.

Suggested Citation

  • S Y Sohn, 2006. "Random effects logistic regression model for ranking efficiency in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(11), pages 1289-1299, November.
    • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:11:d:10.1057_palgrave.jors.2602117
    DOI: 10.1057/palgrave.jors.2602117
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palgrave.jors.2602117
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/palgrave.jors.2602117?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. 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.
    2. Finn Førsund & Nikias Sarafoglou, 2002. "On the Origins of Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 23-40, January.
    3. 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.
    4. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    5. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Daniel Friesner & Ron Mittelhammer & Robert Rosenmane, 2006. "Inferring the Latent Incidence of Inefficiency from DEA Estimates and Bayesian Priors," Working Papers 2006-8, School of Economic Sciences, Washington State University.
    2. Nima Mirzaei & Béla Vizvári, 2015. "A New Approach to Reconstruction of Moody’s Rating System for Countries Investment Risk Rating," Journal of Empirical Economics, Research Academy of Social Sciences, vol. 4(3), pages 167-182.
    3. Epure, Mircea & Kerstens, Kristiaan & Prior, Diego, 2011. "Bank productivity and performance groups: A decomposition approach based upon the Luenberger productivity indicator," European Journal of Operational Research, Elsevier, vol. 211(3), pages 630-641, June.
    4. S Y Sohn & Y Kim & B T Kim, 2009. "Cost of ownership model for spare engines purchase for the Korean navy acquisition program," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1674-1682, December.
    5. Kim, Yoonseong & Sohn, So Young, 2008. "Random effects model for credit rating transitions," European Journal of Operational Research, Elsevier, vol. 184(2), pages 561-573, January.
    6. Sohn, So Young & Kim, Hong Sik, 2007. "Random effects logistic regression model for default prediction of technology credit guarantee fund," European Journal of Operational Research, Elsevier, vol. 183(1), pages 472-478, November.
    7. Seyed Ali Rakhshan, 2017. "Efficiency ranking of decision making units in data envelopment analysis by using TOPSIS-DEA method," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(8), pages 906-918, August.
    8. Eliane Gomes & João Soares de Mello & Geraldo Souza & Lidia Angulo Meza & João Mangabeira, 2009. "Efficiency and sustainability assessment for a group of farmers in the Brazilian Amazon," Annals of Operations Research, Springer, vol. 169(1), pages 167-181, July.
    9. Friesner, Daniel & Mittelhammer, Ron & Rosenman, Robert, 2013. "Inferring the incidence of industry inefficiency from DEA estimates," European Journal of Operational Research, Elsevier, vol. 224(2), pages 414-424.

    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. Sebastian Kohl & Jan Schoenfelder & Andreas Fügener & Jens O. Brunner, 2019. "The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals," Health Care Management Science, Springer, vol. 22(2), pages 245-286, June.
    2. Ülengin, Füsun & Kabak, Özgür & Önsel, Sule & Aktas, Emel & Parker, Barnett R., 2011. "The competitiveness of nations and implications for human development," Socio-Economic Planning Sciences, Elsevier, vol. 45(1), pages 16-27, March.
    3. Jesús Peiró-Palomino & Andrés J. Picazo-Tadeo, 2018. "Assessing well-being in European regions. Does government quality matter?," Working Papers 2018/06, Economics Department, Universitat Jaume I, Castellón (Spain).
    4. Zhicheng Lai & Lei Li & Zhuomin Tao & Tao Li & Xiaoting Shi & Jialing Li & Xin Li, 2023. "Spatio-Temporal Evolution and Influencing Factors of Ecological Well-Being Performance from the Perspective of Strong Sustainability: A Case Study of the Three Gorges Reservoir Area, China," IJERPH, MDPI, vol. 20(3), pages 1-25, January.
    5. Li, Yongjun & Yang, Feng & Liang, Liang & Hua, Zhongsheng, 2009. "Allocating the fixed cost as a complement of other cost inputs: A DEA approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 389-401, August.
    6. Dag Edvardsen & Finn Førsund & Sverre Kittelsen, 2008. "Far out or alone in the crowd: a taxonomy of peers in DEA," Journal of Productivity Analysis, Springer, vol. 29(3), pages 201-210, June.
    7. Soushi Suzuki & Karima Kourtit & Peter Nijkamp, 2017. "The robustness of performance rankings of Asia-Pacific super cities," Asia-Pacific Journal of Regional Science, Springer, vol. 1(1), pages 219-242, April.
    8. Alda A. Henriques & Milton Fontes & Ana S. Camanho & Giovanna D’Inverno & Pedro Amorim & Jaime Gabriel Silva, 2022. "Performance evaluation of problematic samples: a robust nonparametric approach for wastewater treatment plants," Annals of Operations Research, Springer, vol. 315(1), pages 193-220, August.
    9. 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.
    10. 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.
    11. Taylan G. Topcu & Konstantinos Triantis, 2022. "An ex-ante DEA method for representing contextual uncertainties and stakeholder risk preferences," Annals of Operations Research, Springer, vol. 309(1), pages 395-423, February.
    12. Reichmann, Gerhard & Sommersguter-Reichmann, Margit, 2006. "University library benchmarking: An international comparison using DEA," International Journal of Production Economics, Elsevier, vol. 100(1), pages 131-147, March.
    13. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    14. M I Gonzalez-Bravo, 2007. "Prior-Ratio-Analysis procedure to improve data envelopment analysis for performance measurement," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(9), pages 1214-1222, September.
    15. Victor Podinovski & Emmanuel Thanassoulis, 2007. "Improving discrimination in data envelopment analysis: some practical suggestions," Journal of Productivity Analysis, Springer, vol. 28(1), pages 117-126, October.
    16. Victoria Wojcik & Harald Dyckhoff & Marcel Clermont, 2019. "Is data envelopment analysis a suitable tool for performance measurement and benchmarking in non-production contexts?," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 559-595, December.
    17. Vladimír Holý & Karel Šafr, 2018. "Are economically advanced countries more efficient in basic and applied research?," 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. 26(4), pages 933-950, December.
    18. Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
    19. Ramon Sala-Garrido & Manuel Mocholí-Arce & María Molinos-Senante, 2021. "Assessing the Quality of Service of Water Companies: a ‘Benefit of the Doubt’ Composite Indicator," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(1), pages 371-387, May.
    20. Rita Bastião & Nuno de Sousa Pereira, 2020. "Performance in the Delivery of Primary Health Care Services: A Longitudinal Analysis," CEF.UP Working Papers 2002, Universidade do Porto, Faculdade de Economia do Porto.

    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:pal:jorsoc:v:57:y:2006:i:11:d:10.1057_palgrave.jors.2602117. 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.palgrave-journals.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.