دانلود رایگان مقاله انگلیسی ارزیابی بهره وری حد واسط در تحلیل پوششی داده ها بر اساس نظریه چشم انداز - الزویر 2019

Abstract

Cross-efficiency evaluation in data envelopment analysis (DEA) is a useful tool in evaluating the performance of decision-making units (DMUs). It is generally assumed that decision makers (DMs) are completely rational in common cross-efficiency evaluation models, which fail to consider the DM’s risk attitude that plays an important role in the evaluation process. To fill this gap, we investigate the cross-efficiency evaluation in DEA based on prospect theory. First, we introduce a prospect value of the DMU to capture the non-rational psychological aspects of a DM under risk. Second, based on the prospect value, we propose a new cross-efficiency model termed the prospect cross-efficiency (PCE) model. Particularly, some existing cross-efficiency evaluation models can be deemed as the special cases of the PCE model with suitable adjustments of the parameters. Furthermore, this paper provides an empirical example to evaluate cross-efficiency with several selected universities directly managed by the Ministry of Education of China to illustrate the effectiveness of the PCE model in ranking DMUs.

 Conclusions and discussions

Cross-efficiency in DEA has been widely accepted as a useful tool for evaluating the performance of DMUs and has been used in a variety of theoretical studies and practical applications. However, common cross-efficiency evaluation models assume that DMs are completely rational and generally fail to consider the risk attitude of a DM that plays an important role in the evaluation process. Noting that prospect theory can capture the non-rational psychological aspects of DMs under risk, this paper investigates the cross-efficiency evaluation based on prospect theory and proposes a novel cross-efficiency model termed the PCE model in which the prospect values of each DMU are introduced. The PCE model can capture the risk attitude of the DMs and maintains a certain degree of fairness. That is, the secondary goal for cross-efficiency evaluation is set without the use of information from other DMUs. Furthermore, this paper provides a numerical example to illustrate the potential applications of the PCE model and its effectiveness in ranking DMUs compared with several classical cross-efficiency models. The case study shows that the risk preference of DMs characterized by the parameters  ,  , and  in the PCE model influences the results of performance evaluation. To the best of our knowledge, this is the first time that prospect theory is used to evaluate efficiency in DEA. The proposed approach can be effectively applied to different evaluation problems, such as investment selection and financial management. Nevertheless, we do not consider the regret of DMs when using the PCE model for evaluation problems. Despite our interest on introducing the regret theory in the cross-efficiency model, we leave that point for future research since it may result in sophisticated calculations and our model cannot be applied to an extended framework.