Efficiency ranking with common set of weights based on data envelopment analysis and satisfaction degree
Yanling Dong,
Ya Chen and
Yongjun Li
International Journal of Information and Decision Sciences, 2014, vol. 6, issue 4, 354-368
Abstract:
Traditional DEA models allow individual decision-making units (DMUs) to arbitrarily determine the weights of all variables to calculate their efficiencies. This flexibility in selecting the weights is a great advantage for many DMUs, but it also brings some defects such as non-uniqueness of weights sets and the appearance of zero-value weights. Different sets of weights to calculate efficiencies violate the requirement that DMUs should be compared on the same base, leading to the efficiency ranking being not accepted by decision-makers. In this paper, we provide a DEA-based approach for obtaining DMUs' efficiencies, which assumes that DMUs are collective rationality and its objective is to maximise the satisfaction degrees of all the DMUs. Then, we provide a maxmin model and two corresponding algorithms for generating the common set of weights (CSW). Lastly, the proposed approach is applied to the ranking of 17 forest districts and is compared with other methods.
Keywords: data envelopment analysis; DEA; decision making units; DMUs; efficiency scores; zero-value weights; collective rationality; common set of weights; CSW; efficiency ranking; max min model; satisfaction degree; forest districts. (search for similar items in EconPapers)
Date: 2014
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