IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v230y2013i3p634-642.html
   My bibliography  Save this article

Incorporating performance measures with target levels in data envelopment analysis

Author

Listed:
  • Lim, Sungmook
  • Zhu, Joe

Abstract

Data envelopment analysis (DEA) is a technique for evaluating relative efficiencies of peer decision making units (DMUs) which have multiple performance measures. These performance measures have to be classified as either inputs or outputs in DEA. DEA assumes that higher output levels and/or lower input levels indicate better performance. This study is motivated by the fact that there are performance measures (or factors) that cannot be classified as an input or output, because they have target levels with which all DMUs strive to achieve in order to attain the best practice, and any deviations from the target levels are not desirable and may indicate inefficiency. We show how such performance measures with target levels can be incorporated in DEA. We formulate a new production possibility set by extending the standard DEA production possibility set under variable returns-to-scale assumption based on a set of axiomatic properties postulated to suit the case of targeted factors. We develop three efficiency measures by extending the standard radial, slacks-based, and Nerlove–Luenberger measures. We illustrate the proposed model and efficiency measures by applying them to the efficiency evaluation of 36 US universities.

Suggested Citation

  • Lim, Sungmook & Zhu, Joe, 2013. "Incorporating performance measures with target levels in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 230(3), pages 634-642.
    • Handle: RePEc:eee:ejores:v:230:y:2013:i:3:p:634-642
    DOI: 10.1016/j.ejor.2013.04.051
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221713003652
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2013.04.051?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. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, December.
    2. Wenbin Liu & John Sharp & Zhongmin Wu, 2006. "Preference, Production and Performance in Data Envelopment Analysis," Annals of Operations Research, Springer, vol. 145(1), pages 105-127, July.
    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. William W. Cooper & Lawrence M. Seiford & Joe Zhu, 2011. "Data Envelopment Analysis: History, Models, and Interpretations," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 1-39, Springer.
    5. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    6. Breu, Theodore M. & Raab, Raymond L., 1994. "Efficiency and perceived quality of the nation's "top 25" National Universities and National Liberal Arts Colleges: An application of data envelopment analysis to higher education," Socio-Economic Planning Sciences, Elsevier, vol. 28(1), pages 33-45.
    7. 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.
    8. 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.
    9. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    10. Colbert, Amy & Levary, Reuven R. & Shaner, Michael C., 2000. "Determining the relative efficiency of MBA programs using DEA," European Journal of Operational Research, Elsevier, vol. 125(3), pages 656-669, September.
    11. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    12. 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.
    13. Cook, Wade D. & Zhu, Joe, 2007. "Classifying inputs and outputs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 180(2), pages 692-699, July.
    14. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, 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. Wade D. Cook & Chuanyin Guo & Wanghong Li & Zhepeng Li & Liang Liang & Joe Zhu, 2017. "Efficiency Measurement of Multistage Processes: Context Dependent Numbers of Stages," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(06), pages 1-18, December.
    2. Aparicio, Juan & Pastor, Jesus T., 2014. "Closest targets and strong monotonicity on the strongly efficient frontier in DEA," Omega, Elsevier, vol. 44(C), pages 51-57.
    3. Mustapha Daruwana Ibrahim & Sahand Daneshvar & Hüseyin Güden & Bela Vizvari, 2020. "Target setting in data envelopment analysis: efficiency improvement models with predefined inputs/outputs," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1319-1336, December.
    4. Park, Jaehun & Lee, Dongha & Zhu, Joe, 2014. "An integrated approach for ship block manufacturing process performance evaluation: Case from a Korean shipbuilding company," International Journal of Production Economics, Elsevier, vol. 156(C), pages 214-222.
    5. Fafaliou, Irene & Zervopoulos, Panagiotis, 2014. "Strategy in practice: a quantitative approach to target setting," MPRA Paper 54054, University Library of Munich, Germany.
    6. Ya Chen & Wade D. Cook & Juan Du & Hanhui Hu & Joe Zhu, 2017. "Bounded and discrete data and Likert scales in data envelopment analysis: application to regional energy efficiency in China," Annals of Operations Research, Springer, vol. 255(1), pages 347-366, August.
    7. Zervopoulos, Panagiotis D. & Brisimi, Theodora S. & Emrouznejad, Ali & Cheng, Gang, 2016. "Performance measurement with multiple interrelated variables and threshold target levels: Evidence from retail firms in the US," European Journal of Operational Research, Elsevier, vol. 250(1), pages 262-272.
    8. Li, Yongjun & Xie, Jianhui & Wang, Meiqiang & Liang, Liang, 2016. "Super efficiency evaluation using a common platform on a cooperative game," European Journal of Operational Research, Elsevier, vol. 255(3), pages 884-892.

    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. 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.
    2. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    3. 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.
    4. Jie Wu & Zhixiang Zhou, 2015. "A mixed-objective integer DEA model," Annals of Operations Research, Springer, vol. 228(1), pages 81-95, May.
    5. Shih-Heng Yu, 2019. "Benchmarking and Performance Evaluation Towards the Sustainable Development of Regions in Taiwan: A Minimum Distance-Based Measure with Undesirable Outputs in Additive DEA," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(3), pages 1323-1348, August.
    6. 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.
    7. 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.
    8. Imanirad, Raha & Cook, Wade D. & Aviles-Sacoto, Sonia Valeria & Zhu, Joe, 2015. "Partial input to output impacts in DEA: The case of DMU-specific impacts," European Journal of Operational Research, Elsevier, vol. 244(3), pages 837-844.
    9. Maria Silva Portela & Pedro Borges & Emmanuel Thanassoulis, 2003. "Finding Closest Targets in Non-Oriented DEA Models: The Case of Convex and Non-Convex Technologies," Journal of Productivity Analysis, Springer, vol. 19(2), pages 251-269, April.
    10. Kao, Chiang, 2020. "Measuring efficiency in a general production possibility set allowing for negative data," European Journal of Operational Research, Elsevier, vol. 282(3), pages 980-988.
    11. Podinovski, Victor V. & Kuosmanen, Timo, 2011. "Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions," European Journal of Operational Research, Elsevier, vol. 211(3), pages 577-585, June.
    12. 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.
    13. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    14. Jesus Pastor & C. Lovell & Juan Aparicio, 2012. "Families of linear efficiency programs based on Debreu’s loss function," Journal of Productivity Analysis, Springer, vol. 38(2), pages 109-120, October.
    15. Bretholt, Abraham & Pan, Jeh-Nan, 2013. "Evolving the latent variable model as an environmental DEA technology," Omega, Elsevier, vol. 41(2), pages 315-325.
    16. Laura Calzada-Infante & Ana María López-Narbona & Alberto Núñez-Elvira & Javier Orozco-Messana, 2020. "Assessing the Efficiency of Sustainable Cities Using an Empirical Approach," Sustainability, MDPI, vol. 12(7), pages 1-13, March.
    17. Sanjeet Singh & Prabhat Ranjan, 2018. "Efficiency analysis of non-homogeneous parallel sub-unit systems for the performance measurement of higher education," Annals of Operations Research, Springer, vol. 269(1), pages 641-666, October.
    18. Tao Xu & Jianxin You & Hui Li & Luning Shao, 2020. "Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review," Energies, MDPI, vol. 13(14), pages 1-20, July.
    19. Akther, Syed & Fukuyama, Hirofumi & Weber, William L., 2013. "Estimating two-stage network Slacks-based inefficiency: An application to Bangladesh banking," Omega, Elsevier, vol. 41(1), pages 88-96.
    20. Cui, Qiang & Jin, Zi-yin, 2020. "Airline environmental efficiency measures considering negative data: An application of a modified network Modified Slacks-based measure model," Energy, Elsevier, vol. 207(C).

    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:eee:ejores:v:230:y:2013:i:3:p:634-642. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.