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Weight-restricted DEA in action: from expert opinions to mathematical models

Author

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  • T Joro

    (University of Alberta School of Business, Edmonton)

  • E-J Viitala

    (Finnish Forest Research Institute)

Abstract

A common problem in real-world DEA applications is that all inputs and outputs may not be equally relevant to the organizations analysed and their stakeholders. In many cases, one is also faced with a data set where the decision-making units do not clearly outnumber the quantity of inputs and outputs. This study reports an application where DEA embellished with weight restrictions is used to analyse the efficiency of public organizations to overcome the above-mentioned problems. Whereas there are numerous documented applications of weight-restricted DEA in the literature, the process of defining the actual weight restrictions is seldom described. However, that part — defining the actual weights restrictions based on price, preference or value information — is the most difficult step involved in using the weight-restricted DEA. Comparing various weight restriction schemes with real data suggests that the ability to consider and include preference information in DEA adds important insights into the analysis.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:8:d:10.1057_palgrave.jors.2601752
    DOI: 10.1057/palgrave.jors.2601752
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    2. Førsund, Finn, 2015. "Economic Perspectives on DEA," Memorandum 10/2015, Oslo University, Department of Economics.
    3. Milica Maricic & Jose A. Egea & Veljko Jeremic, 2019. "A Hybrid Enhanced Scatter Search—Composite I-Distance Indicator (eSS-CIDI) Optimization Approach for Determining Weights Within Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(2), pages 497-537, July.
    4. 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.
    5. A. Guerrini & G. Romano & L. Carosi & F. Mancuso, 2017. "Cost Savings in Wastewater Treatment Processes: the Role of Environmental and Operational Drivers," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(8), pages 2465-2478, June.
    6. Edirisinghe, N.C.P. & Zhang, X., 2010. "Input/output selection in DEA under expert information, with application to financial markets," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1669-1678, December.
    7. 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.
    8. Panagiotis Ravanos & Giannis Karagiannis, 2022. "In search for the most preferred solution in value efficiency analysis," Journal of Productivity Analysis, Springer, vol. 58(2), pages 203-220, December.
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