Abstract
Data envelopment analysis (DEA) is an effective mathematical method for evaluating the efficiencies of decision-making units (DMUs). However, in the process of cross-efficiency evaluation, DEA models commonly neglect the regret aversion psychological characteristics of decision makers (DMs). Therefore, this paper focuses on the construction of regret-rejoice cross-efficiency linguistic distribution DEA (RCE-LDDEA) method with regret theory, in which the input and output data by means of linguistic distributions and the regret aversion psychological characteristics of DMs are considered. First, a linguistic distribution DEA model is proposed to derive the self-evaluation efficiencies of DMUs with linguistic distribution evaluation information. Then, based on regret theory, a regret-rejoice cross-efficiency evaluation (RCEE) model is developed to evaluate the cross-efficiencies of DMUs. Subsequently, based on the regret-rejoice super-efficiency evaluation (RSEE) model, a RCE-LDDEA method is designed to generate the complete ranking of DMUs. Finally, an example for evaluating performance of 10 public hospitals in China is provided to illustrate the implementation of the proposed RCE-LDDEA method. The stability and advantages of the proposed RCE-LDDEA method is performed by sensitivity analysis and comparative analysis.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: 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.