Abstract:One of the drawbacks of Data Envelopment Analysis ( DEA ) is the problem of lack of discrimination among efficient Decision Making Units ( DMUs ) and hence yielding many numbers of Decision Making Units as efficient. The main purpose of this paper is to overcom More
Abstract:One of the drawbacks of Data Envelopment Analysis ( DEA ) is the problem of lack of discrimination among efficient Decision Making Units ( DMUs ) and hence yielding many numbers of Decision Making Units as efficient. The main purpose of this paper is to overcome this inability. In this paper, we explain new methods based on stability ranges for weights of inputs and outputs, these weights are the weights, that Decision Making Units remain efficient. For illustration numerical example is given.
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The Malmquist Index is the prominent Index for measuring the productivity change of Decision Making Units (DMUs) in multiple time periods that use Data Envelopment Analysis (DEA) models with Variable Return to Scale (VRS) and Constant Return to Scale (CRS) technology. O More
The Malmquist Index is the prominent Index for measuring the productivity change of Decision Making Units (DMUs) in multiple time periods that use Data Envelopment Analysis (DEA) models with Variable Return to Scale (VRS) and Constant Return to Scale (CRS) technology. One of the drawbacks of DEA is the problem of lack of discrimination among efficient DMUs and hence yielding many numbers of DMUs as efficient. The main purpose of this paper is to overcome this inability. In this paper, we compute the Malmquist Index based on means of weights evaluation, and by using this method we can rank DMUs by logical criteria. For illustration numerical example is given.
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