AUA Public Events
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Data Envelopment Analysis
March 21 @ 7:00 pm - 8:00 pm
About the Event:
Data Envelopment Analysis (DEA) was initiated by Charnes, Cooper and Rhodes in 1978 in their seminal paper Charnes et al. (1978). The paper extended by means of linear programming production economics concepts of empirical efficiency put forth some twenty years earlier by Farrel (1957). DEA is a non-parametric method to evaluate relative efficiency of organizational units called decision making units (DMUs) where each DMU utilizes multiple inputs to produce multiple outputs. DEA was initially developed as a method for evaluating the relative efficiencies of organizations such as business firms, government agencies, hospital departments, restaurants, universities, etc. Such evaluations take a different of forms in traditional and customary analyses. Different examples include cost per unit, profit per unit, satisfaction per unit, and so on, which are measures stated in the form of a ratio as follows,
The above mentioned measure is commonly used as efficiency. DEA attempts to obtain an output-to-input ratio value which takes account of all outputs and all inputs. Combining of all inputs and all outputs to achieve a single ratio helps to avoid imputing gains to one factor that are really attributable to some other factor. Different types of problems and limitations can be seen in traditional attempts to evaluate productivity or efficiency when multiple inputs and multiple outputs need to be taken into account. The relatively approach considered in DEA does not require the Decision Making Units (DMUs) to prescribe weights to be attached to each input and output, as traditional approaches, and it also does not require prescribing the functional forms that are needed in statistical regression approaches to these topics. Relaxing conditions on some of the problems of traditional methods makes it easier to deal with complex problems and to deal with many managerial and policy contexts. Moreover, the mathematical structure of DEA makes it easier to encounter with analyses and interpretations.
About the Speaker:
Sevan Sohraiee is an Assistant Professor at Department of Mathematics of Islamic Azad University, Tehran, Iran. His researches include Data Envelopment Analysis, Game Theory and Optimization Theory.
Sohraiee got his Master’s and PhD in Applied Mathematics from Islamic Azad University.
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