IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v48y2014i1p20-28.html
   My bibliography  Save this article

The appreciative democratic voice of DEA: A case of faculty academic performance evaluation

Author

Listed:
  • Oral, Muhittin
  • Oukil, Amar
  • Malouin, Jean-Louis
  • Kettani, Ossama

Abstract

Data envelopment analysis (DEA) is in fact more than just being an instrument for measuring the relative efficiencies of a group of decision making units (DMU). DEA models are also means of expressing appreciative democratic voices of DMUs. This paper proposes a methodology for allocating premium points to a group of professors using three models sequentially: (1) a DEA model for appreciative academic self-evaluation, (2) a DEA model for appreciative academic cross-evaluation, and (3) a Non-DEA model for academic rating of professors for the purpose of premium allocations. The premium results, called DEA results, are then compared with the premium points “nurtured” by the Dean, called N bonus points. After comparing DEA results and N bonus points, the Dean reassessed his initial bonus points and provided new ones – called DEA-N decisions. The experience indicates that judgmental decisions (Dean's evaluations) can be enhanced by making use of formal models (DEA and Non-DEA models). Moreover, the appreciative and democratic voices of professors are virtually embedded in the DEA models.

Suggested Citation

  • Oral, Muhittin & Oukil, Amar & Malouin, Jean-Louis & Kettani, Ossama, 2014. "The appreciative democratic voice of DEA: A case of faculty academic performance evaluation," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 20-28.
  • Handle: RePEc:eee:soceps:v:48:y:2014:i:1:p:20-28
    DOI: 10.1016/j.seps.2013.08.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012113000505
    Download Restriction: Full text for ScienceDirect subscribers only

    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. De Witte, Kristof & Rogge, Nicky & Cherchye, Laurens & Van Puyenbroeck, Tom, 2013. "Economies of scope in research and teaching: A non-parametric investigation," Omega, Elsevier, vol. 41(2), pages 305-314.
    2. Yang, Feng & Ang, Sheng & Xia, Qiong & Yang, Chenchen, 2012. "Ranking DMUs by using interval DEA cross efficiency matrix with acceptability analysis," European Journal of Operational Research, Elsevier, vol. 223(2), pages 483-488.
    3. Oral, Muhittin & Kettani, Ossama & Cinar, Unver, 2001. "Project evaluation and selection in a network of collaboration: A consensual disaggregation multi-criterion approach," European Journal of Operational Research, Elsevier, vol. 130(2), pages 332-346, April.
    4. Oral, Muhittin, 2010. "E-DEA: Enhanced data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 207(2), pages 916-926, December.
    5. Sun, Minghe, 2002. "A multiple objective programming approach for determining faculty salary equity adjustments," European Journal of Operational Research, Elsevier, vol. 138(2), pages 302-319, April.
    6. Muhittin Oral & Ossama Kettani & Pascal Lang, 1991. "A Methodology for Collective Evaluation and Selection of Industrial R&D Projects," Management Science, INFORMS, vol. 37(7), pages 871-885, July.
    7. Wang, Ying-Ming & Chin, Kwai-Sang, 2011. "The use of OWA operator weights for cross-efficiency aggregation," Omega, Elsevier, vol. 39(5), pages 493-503, October.
    8. Liang, Liang & Wu, Jie & Cook, Wade D. & Zhu, Joe, 2008. "Alternative secondary goals in DEA cross-efficiency evaluation," International Journal of Production Economics, Elsevier, vol. 113(2), pages 1025-1030, June.
    9. 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.
    10. Green, Rodney H. & Doyle, John R. & Cook, Wade D., 1996. "Preference voting and project ranking using DEA and cross-evaluation," European Journal of Operational Research, Elsevier, vol. 90(3), pages 461-472, May.
    11. Doyle, J. R. & Green, R. H. & Cook, W. D., 1995. "Upper and Lower Bound Evaluation of Multiattribute Objects: Comparison Models Using Linear Programming," Organizational Behavior and Human Decision Processes, Elsevier, vol. 64(3), pages 261-273, December.
    12. Liang Liang & Jie Wu & Wade D. Cook & Joe Zhu, 2008. "The DEA Game Cross-Efficiency Model and Its Nash Equilibrium," Operations Research, INFORMS, vol. 56(5), pages 1278-1288, October.
    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. Abolghasem, Sepideh & Gómez-Sarmiento, Juliana & Medaglia, Andrés L. & Sarmiento, Olga L. & González, Andrés D. & Díaz del Castillo, Adriana & Rozo-Casas, Juan F. & Jacoby, Enrique, 2018. "A DEA-centric decision support system for evaluating Ciclovía-Recreativa programs in the Americas," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 90-101.
    2. Oukil, Amar, 2020. "Exploiting value system multiplicity and preference voting for robust ranking," Omega, Elsevier, vol. 94(C).
    3. Biresh K Sahoo & Ramadhar Singh & Bineet Mishra & Krithiga Sankaran, 2015. "Research Productivity in Management Schools of India: A Directional Benefit-of-Doubt Model Analysis," Working Papers id:7139, eSocialSciences.
    4. Shiang-Tai Liu, 2018. "A DEA ranking method based on cross-efficiency intervals and signal-to-noise ratio," Annals of Operations Research, Springer, vol. 261(1), pages 207-232, February.
    5. Sung-Shun Weng & Yang Liu & Yen-Ching Chuang, 2019. "Reform of Chinese Universities in the Context of Sustainable Development: Teacher Evaluation and Improvement Based on Hybrid Multiple Criteria Decision-Making Model," Sustainability, MDPI, Open Access Journal, vol. 11(19), pages 1-23, October.
    6. Lei Chen & Ying-Ming Wang & Yan Huang, 2020. "Cross-efficiency aggregation method based on prospect consensus process," Annals of Operations Research, Springer, vol. 288(1), pages 115-135, May.
    7. Shiang-Tai Liu & Yueh-Chiang Lee, 0. "Fuzzy measures for fuzzy cross efficiency in data envelopment analysis," Annals of Operations Research, Springer, vol. 0, pages 1-30.
    8. Giannis Karagiannis & Georgia Paschalidou, 2017. "Assessing research effectiveness: a comparison of alternative nonparametric models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 456-468, April.
    9. Sahoo, Biresh K. & Singh, Ramadhar & Mishra, Bineet & Sankaran, Krithiga, 2017. "Research productivity in management schools of India during 1968-2015: A directional benefit-of-doubt model analysis," Omega, Elsevier, vol. 66(PA), pages 118-139.

    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:soceps:v:48:y:2014:i:1:p:20-28. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Haili He). General contact details of provider: http://www.elsevier.com/locate/seps .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.