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A general model framework for DEA

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  • Kleine, A.

Abstract

Analyzing the efficiency of actions, productions, or organizational units is a fundamental problem of economic research. Data Envelopment Analysis (DEA) is designed to measure the efficiency of decision making units. The set of reference units in DEA is generated on the assumption of a specific production technology. From a decision theoretical view, DEA models are based on scalarizing functions known from Multi-Criteria Decision Making. On these grounds it is possible to formulate a general DEA model. This formulation is a basis for well-known and new DEA approaches, as a classification scheme for DEA models shows.

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  • Kleine, A., 2004. "A general model framework for DEA," Omega, Elsevier, vol. 32(1), pages 17-23, February.
  • Handle: RePEc:eee:jomega:v:32:y:2004:i:1:p:17-23
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    Cited by:

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    5. Dyckhoff, Harald & Souren, Rainer, 2022. "Integrating multiple criteria decision analysis and production theory for performance evaluation: Framework and review," European Journal of Operational Research, Elsevier, vol. 297(3), pages 795-816.
    6. Piran, Fabio Antonio Sartori & Lacerda, Daniel Pacheco & Camargo, Luis Felipe Riehs & Viero, Carlos Frederico & Dresch, Aline & Cauchick-Miguel, Paulo Augusto, 2016. "Product modularization and effects on efficiency: An analysis of a bus manufacturer using data envelopment analysis (DEA)," International Journal of Production Economics, Elsevier, vol. 182(C), pages 1-13.
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    8. Walter Briec & Kristiaan Kerstens & Ignace Van de Woestyne, 2022. "Nonconvexity in Production and Cost Functions: An Exploratory and Selective Review," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 18, pages 721-754, Springer.
    9. Eugenia Nissi & Massimiliano Giacalone & Carlo Cusatelli, 2019. "The Efficiency of the Italian Judicial System: A Two Stage Data Envelopment Analysis Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 395-407, November.
    10. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
    11. E. Musoke & B.L. Yawe & J.D. Ssentamu, 2023. "Determinants of technical efficiency of health systems in African least developed countries: A two-stage data envelopment analysis (DEA) approach," Journal of Economic Policy and Management Issues, JEPMI, vol. 2(1), pages 59-75.
    12. Jhong-You Huang & Wann-Ming Wey, 2019. "Application of Big Data and Analytic Network Process for the Adaptive Reuse Strategies of School Land," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(3), pages 1075-1102, April.
    13. Halická, Margaréta & Trnovská, Mária, 2021. "A unified approach to non-radial graph models in data envelopment analysis: common features, geometry, and duality," European Journal of Operational Research, Elsevier, vol. 289(2), pages 611-627.
    14. Ehrgott, Matthias & Tind, Jørgen, 2009. "Column generation with free replicability in DEA," Omega, Elsevier, vol. 37(5), pages 943-950, October.
    15. Anna Ćwiąkała-Małys & Violetta Nowak, 2009. "Classification of Data Envelopment Analysis models," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 19(3), pages 5-18.
    16. Szczepan Figiel & Jacek Michalak & Anna Rutkowska, 2018. "Efektywność funkcjonowania urzędów wojewódzkich w Polsce w ujęciu nieparametrycznym," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 161-179.
    17. Andreas Dellnitz & Andreas Kleine & Wilhelm Rödder, 2018. "CCR or BCC: what if we are in the wrong model?," Journal of Business Economics, Springer, vol. 88(7), pages 831-850, September.
    18. Harald Dyckhoff, 2019. "Multi-criteria production theory: convexity propositions and reasonable axioms," Journal of Business Economics, Springer, vol. 89(6), pages 719-735, August.
    19. Maryam Bagherikahvarin & Yves Smet, 2017. "Determining new possible weight values in PROMETHEE: a procedure based on data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(5), pages 484-495, May.

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