To evaluate the performance of decision making units (DMUs), data envelopment analysis (DEA) was introduced. Basically, the traditional DEA scheme calculates the best relative efficiency score (i.e., the “optimistic” efficiency) of each DMU with the most favorable weights. A decision maker may be unable to compare and fully rank the efficiencies of different DMUs that are calculated using these potentially distinct sets of weights on the same basis. Based on the literature, the assignable worst relative efficiency score (i.e., the “pessimistic” efficiency) for each DMU can also be determined. In this paper, the best and the worst relative efficiencies are considered simultaneously. To measure the overall performance of the DMUs, an integration of both the best and the worst relative efficiencies is considered in the form of an interval. The advantage of this efficiency interval is that it provides all of the possible efficiency values and an expanded overview to the decision maker. The proposed method determines the lower- and upper-bounds of the interval efficiency over a common set of weights. To demonstrate the implementation of the introduced method, a numerical example is provided.
This study uses the data envelopment analysis (DEA) interval efficiency to determine the priorities of eight perceived intelligence parameters skills by considering the people with epilepsy (PWE)'s demographic background. The results of this study help the PWE to identify their strengths and weaknesses where to improve the chances of employability in the job market and to improve their inherent skills for suitable employment. The ranking of PWE's intelligence parameters would describe the status quo of epilepsy sufferers with respect to their intelligence level. Gardner had introduced related activities, products, and suitable careers to each of eight intelligence parameters. Therefore, training the various recommended activities for an epileptic sufferer is paramount in order to be successful in the workplace.
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