Abstract
Cross-efficiency evaluation approaches and common set of weights (CSW) approaches have long been suggested as two of the more important and effective methods for the ranking of decision making units (DMUs) in data envelopment analysis (DEA). The former emphasizes the flexibility of evaluation and its weights are asymmetric, while the latter focuses on the standardization of evaluation and its weights are symmetrical. As a compromise between these two approaches, this paper proposes a cross-efficiency evaluation method that is based on two types of flexible evaluation criteria balanced on interval weights. The evaluation criteria can be regarded as macro policy—or means of regulation—according to the industry’s current situation. Unlike current cross-efficiency evaluation methods, which tend to choose the set of weights for peer evaluation based on certain preferences, the cross-efficiency evaluation method based on evaluation criterion determines one set of input and output weights for each DMU. This is done by minimizing the difference between the weights of the DMU and the evaluation criteria, thus ensuring that the cross-evaluation of all DMUs for evaluating peers is as consistent as possible. This method also eliminates prejudice and arbitrariness from peer evaluations. As a result, the proposed cross-efficiency evaluation method not only looks for non-zero weights, but also ranks efficient DMUs completely. The proposed DEA model can be further extended to seek a common set of weights for all DMUs. Numerical examples are provided to illustrate the applications of the cross-efficiency evaluation method based on evaluation criterion in DEA ranking.
Highlights
Data envelopment analysis (DEA) is a practical methodology originally proposed by Charnes et al [1]
Which aims to find a set of input and output weights that are most favourable to DMUk
Existing DEA models for cross-efficiency evaluation tend to choose the set of weights for peer evaluating using subjective attitudes, without an objective evaluation criterion as a reference point for peer evaluation
Summary
Data envelopment analysis (DEA) is a practical methodology originally proposed by Charnes et al [1]. Other cross-efficiency evaluation methods are discussed in Wu and Chu [8], Oral et al [16], Oukil [17], Carrillo [18], and Shi et al [19] Another remedy is the common set of weights (CSW) approach in DEA, which was first suggested by Cook et al [20]. From the literature review above, all the cross-efficiency evaluation methods are formulated so that each DMU chooses one set of weights determined by the CCR model (self-evaluation model proposed by Charnes, Cooper and Rhodes) that has alternate optima solutions. The proposed method based on an evaluation criterion determines one set of input and output weights for each DMU.
Sign-in/Register to view highlights & summary 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 callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
