<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></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.

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

Proceedings of the International Conference on Business Excellence

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The following study is, in addition to a reassessment of literature and an analysis based on non-parametrical techniques based on linear programming. The...

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

Published Online: Jun 15, 2018

Page range: 533 - 543

DOI: https://doi.org/10.2478/picbe-2018-0048

Keywords
efficiency, productivity, technical productive efficiency, non-parametrical techniques, Data Envelopment Analysis, production border, constant and variable return to the scale

© 2018 Iulian Lita, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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

Published Online: Jun 15, 2018

Page range: 533 - 543

DOI: https://doi.org/10.2478/picbe-2018-0048

Keywordsefficiency, productivity, technical productive efficiency, non-parametrical techniques, Data Envelopment Analysis, production border, constant and variable return to the scale

© 2018 Iulian Lita, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
efficiency, productivity, technical productive efficiency, non-parametrical techniques, Data Envelopment Analysis, production border, constant and variable return to the scale