摘要
Cross-efficiency evaluation is recognized as an effective way of efficiency assessment for a set of decision making units (DMUs) in the framework of data envelopment analysis (DEA). It has been generally suggested that secondary goals be introduced for cross-efficiency evaluation owing to the non-uniqueness of optimal solutions in self-evaluation. This paper develops a variety of secondary goals in the spirit of promoting balance in the output efficiencies of the DMU under evaluation. The proposed models attempt to make each output contribute as equally as possible to the self-evaluated efficiency. In this way, the weight flexibility can for one thing be reduced by the introduced secondary goals with selections from alternate optimal solutions, in addition to counting on the dilution of flexibility in the subsequent peer-evaluation. The proposed approach might be applicable to evaluation problems in which multiple outputs are considered important and balance is encouraged to put all dimensions into sufficient use. The effectiveness of the proposed approach and its comparisons with some relevant secondary goals are illustrated empirically using numerical examples.
Cross-efficiency evaluation is recognized as an effective way of efficiency assessment for a set of decision making units (DMUs) in the framework of data envelopment analysis (DEA). It has been generally suggested that secondary goals be introduced for cross-efficiency evaluation owing to the non-uniqueness of optimal solutions in self-evaluation. This paper develops a variety of secondary goals in the spirit of promoting balance in the output efficiencies of the DMU under evaluation. The proposed models attempt to make each output contribute as equally as possible to the self-evaluated efficiency. In this way, the weight flexibility can for one thing be reduced by the introduced secondary goals with selections from alternate optimal solutions, in addition to counting on the dilution of flexibility in the subsequent peer-evaluation. The proposed approach might be applicable to evaluation problems in which multiple outputs are considered important and balance is encouraged to put all dimensions into sufficient use. The effectiveness of the proposed approach and its comparisons with some relevant secondary goals are illustrated empirically using numerical examples.
