The Data Envelopment Analysis Method and the influence of a phenomenon in organizational Efficiency: A literature review and the Data Envelopment Contrast Analysis new application

摘要

The purpose of this paper is to provide a literature review of the non-parametric linear programming method Data Envelopment Analysis (DEA) for the evaluation of the efficiency of organizations and to develop a new application of the method under the influence of social phenomena. The research methodology extends to the literature review of the DEA method based on its historical development, the better-known existing models of the process and the proposal to create a new application based on a comparison of efficiency during two or more times periods, in order to study the way a particular phenomenon (such as the economic crisis) affects the efficiency of organizations. The methods of economic evaluation and the benchmarking techniques are summarized in relation to the DEA. The basic DEA theoretical framework is analyzed under the influence of Farell's work in the method's introduction, Charnes, Cooper & Rhodes, Banker, Charnes & Cooper's models as well as other newer models. The concepts of technical efficiency and allocation, fixed and variable return of scale and the graphical solution of the method are analyzed. The method's applications in an environment of financial crisis are also analyzed. A new application (Data Envelopment Contrast Analysis), is developed, which compares the overall efficiency of organizations using efficiency as calculated through comparison of the efficiency of the Decision Making Units during two or more time periods and which may prove useful in the study of the effect of a phenomenon on the efficiency of organizations. The paper is limited by the impact of a social phenomenon which, through the reforms brought on by the phenomenon, affects efficiency and restricts its application in other cases. This paper is original because it combines the already developed method with a new application in order to link a social phenomenon to the operational research and leaves room for further research in the future in order to assess the change in performance under the influence of social phenomena.