Abstract
In this paper, we utilize Data Envelopment Analysis (DEA), which is a linear programming-based technique, for evaluating the performance of the teams which operate in the Iranian primer football league. We use Analytical Hierarchy Process (AHP) technique for aggregating the sub-factors which involve in input-output factors, and then DEA is used for calculating the efficiency measures. Also, AHP is used to construct some weight restrictions for increasing the discrimination power of the used DEA model. For calculating the efficiency measures, input-oriented weight-restricted BCC model is utilized.
Highlights
Awareness of the performance scores and analyzing the effectiveness of the units under the control of a manager, using the scientific methods, is one of the most important tools that could help the managers to make better decisions and can be lead in optimal usage of the current resources
Analytical Hierarchy Process (AHP) is usually used for ranking the preferences in an multiple criteria decision making (MCDM) context, in this paper, we address some novel applications of this technique
One of the very important points which must be noticed during using of Data Envelopment Analysis (DEA) for applied purposes is the number of input-output factors compared with the number of the decision making units (DMUs)
Summary
Awareness of the performance scores and analyzing the effectiveness (productivity) of the units under the control of a manager, using the scientific methods, is one of the most important tools that could help the managers to make better decisions and can be lead in optimal usage of the current resources. Experiences show that measuring and analyzing the efficiency of units can lead to a feeling of competitiveness among the subsystems, and this would have a positive effect on the overall performance of the system [1,2]. Data envelopment analysis (DEA) is a non-parametric linear programming-based technique for measuring the relative efficiencies of a set of decision making units (DMUs) which consume multiple inputs to produce multiple outputs. This technique was initially proposed by Charnes et al (CCR model) [3] and was improved by other scholars, especially Banker et al (BCC model) [4]. See monographs [1,2] and the review paper [5] for more details about DEA and its applications
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
