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Using non-parametric technical data envelopment analysis - DEA, for measuring productive technical efficiency

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  • Lita Iulian
  • Stamule Tănase

    (The Bucharest University of Economic Studies, Bucharest, Romania)

Abstract

The following study is, in addition to a reassessment of literature and an analysis based on non-parametrical techniques based on linear programming. The analysis based on the Data Envelopment Analisys (DEA) technique will be used to see whether the model that we have used has a significant importance, if there are any substantial differences between the efficiency scores obtained or estimated through various methods. The theoretical part, based on the DEA technique will be analysed under the influence of both the works of Farell(1957), and also Charnes, Cooper, Rhodes(1978), Banker, Charnes, Cooper(1984) and other newer models. The dissolution of efficiency scores obtained through the CRS-DEA model has been studied for a long time into two different components: One is linked with the scale inefficiency and the other one represents the pure technical inefficiency. This dissolution can be done by using the CRS model with technology when not all the companies are operating at the optimum level, i.e. through the simultaneous application on the same set of data of the CRS and VRS models. In this study, the main non-parametrical Data Envelopment Analysis method is presented (Wu, Fan, Zhou, Zhou, 2012; Halkos, Tzeremes, 2009) and its application on a group of 42 companies (The headquarters of a top commercial bank in Romania - S.C. BRD GROUPE SOCIÉTÉ GÉNÉRALE ), based on the information gained in the years 2016-2017. This paper is original because it combines the already developed method with new techniques, in order to link together economic factors and operational research and leaves more room for future researches with the purpose of further assessing and changing the performance of every decisional unit under the influence of the environmental factors.

Suggested Citation

  • Lita Iulian & Stamule Tănase, 2018. "Using non-parametric technical data envelopment analysis - DEA, for measuring productive technical efficiency," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 12(1), pages 533-543, May.
    • Handle: RePEc:vrs:poicbe:v:12:y:2018:i:1:p:533-543:n:48
    DOI: 10.2478/picbe-2018-0048
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    References listed on IDEAS

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    1. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    2. Mirhedayatian, Seyed Mostafa & Azadi, Majid & Farzipoor Saen, Reza, 2014. "A novel network data envelopment analysis model for evaluating green supply chain management," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 544-554.
    3. Halkos, George Emm. & Tzeremes, Nickolaos G., 2009. "Exploring the existence of Kuznets curve in countries' environmental efficiency using DEA window analysis," Ecological Economics, Elsevier, vol. 68(7), pages 2168-2176, May.
    4. Bampatsou, Christina & Papadopoulos, Savas & Zervas, Efthimios, 2013. "Technical efficiency of economic systems of EU-15 countries based on energy consumption," Energy Policy, Elsevier, vol. 55(C), pages 426-434.
    5. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 1993. "The Measurement of Productive Efficiency: Techniques and Applications," OUP Catalogue, Oxford University Press, number 9780195072181.
    6. 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.
    7. Wu, F. & Fan, L.W. & Zhou, P. & Zhou, D.Q., 2012. "Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis," Energy Policy, Elsevier, vol. 49(C), pages 164-172.
    8. Zhou, P. & Ang, B.W. & Zhou, D.Q., 2012. "Measuring economy-wide energy efficiency performance: A parametric frontier approach," Applied Energy, Elsevier, vol. 90(1), pages 196-200.
    9. Mukherjee, Kankana, 2008. "Energy use efficiency in U.S. manufacturing: A nonparametric analysis," Energy Economics, Elsevier, vol. 30(1), pages 76-96, January.
    10. Mukherjee, Kankana, 2008. "Energy use efficiency in the Indian manufacturing sector: An interstate analysis," Energy Policy, Elsevier, vol. 36(2), pages 662-672, February.
    11. Yan, Hong & Wei, Quanling & Hao, Gang, 2002. "DEA models for resource reallocation and production input/output estimation," European Journal of Operational Research, Elsevier, vol. 136(1), pages 19-31, January.
    12. Alene, Arega D. & Manyong, Victor M. & Gockowski, James, 2006. "The production efficiency of intercropping annual and perennial crops in southern Ethiopia: A comparison of distance functions and production frontiers," Agricultural Systems, Elsevier, vol. 91(1-2), pages 51-70, November.
    13. Monchuk, Daniel C. & Chen, Zhuo & Bonaparte, Yosef, 2010. "Explaining production inefficiency in China's agriculture using data envelopment analysis and semi-parametric bootstrapping," China Economic Review, Elsevier, vol. 21(2), pages 346-354, June.
    14. Reinhard, Stijn & Knox Lovell, C. A. & Thijssen, Geert J., 2000. "Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA," European Journal of Operational Research, Elsevier, vol. 121(2), pages 287-303, March.
    15. Fare, R. & Grabowski, R. & Grosskopf, S. & Kraft, S., 1997. "Efficiency of a fixed but allocatable input: A non-parametric approach," Economics Letters, Elsevier, vol. 56(2), pages 187-193, October.
    16. 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.
    17. Khem R. Sharma & PingSun Leung & Halina M. Zaleski, 1999. "Technical, allocative and economic efficiencies in swine production in Hawaii: a comparison of parametric and nonparametric approaches," Agricultural Economics, International Association of Agricultural Economists, vol. 20(1), pages 23-35, January.
    18. Tzouvelekas, Vangelis & Pantzios, Christos J. & Fotopoulos, Christos, 2001. "Technical efficiency of alternative farming systems: the case of Greek organic and conventional olive-growing farms," Food Policy, Elsevier, vol. 26(6), pages 549-569, December.
    19. Mette Asmild & Fai Tam, 2007. "Estimating global frontier shifts and global Malmquist indices," Journal of Productivity Analysis, Springer, vol. 27(2), pages 137-148, April.
    20. Sharma, Khem R. & Leung, PingSun & Zaleski, Halina M., 1999. "Technical, allocative and economic efficiencies in swine production in Hawaii: a comparison of parametric and nonparametric approaches," Agricultural Economics, Blackwell, vol. 20(1), pages 23-35, January.
    21. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
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