This paper proposes a new approach for ranking efficiency units in data envelopment analysis as a modification of the super-efficiency models developed by Tone [1]. The new approach based on slacks-based measure of ef...This paper proposes a new approach for ranking efficiency units in data envelopment analysis as a modification of the super-efficiency models developed by Tone [1]. The new approach based on slacks-based measure of efficiency (SBM) for dealing with objective function used to classify all of the decision-making units allows the ranking of all inefficient DMUs and overcomes the disadvantages of infeasibility. This method also is applied to rank super-efficient scores for the sample of 145 agricultural bank branches in Viet Nam during 2007-2010. We then compare the estimated results from the new SCI model and the exsisting SBM model by using some statistical tests.展开更多
The aim of the paper is to benchmark the performance of the Indian fertilizermanufacturing organizations based on the ranking of efficiencies using a fuzzy data envelopment analysis(FDEA).FDEA has been used to find t...The aim of the paper is to benchmark the performance of the Indian fertilizermanufacturing organizations based on the ranking of efficiencies using a fuzzy data envelopment analysis(FDEA).FDEA has been used to find the relative efficiency and ranking of the fertilizer-manufacturing organizations.The last few years’data have been converted into the fuzzy inputs and outputs as minimum,mean,and maximum values,respectively.The performance of the fertilizer manufacturing organizations is based on the output maximization model of DEA.The frontier organizations set the benchmark for the lagging organizations for further improvement in the performance.This method can also be used to incorporate the data of the several years for multiple inputs and outputs instead of consideration of data of only one year.The proposed approach in this study may help organizations to improve its efficiency to fulfill its goal.展开更多
Environmental variables are widely recognized as a cause of differences in efficiency measurement.However,the existing literature on data envelopment analysis(DEA)in environmental factors ignores the impact of demand ...Environmental variables are widely recognized as a cause of differences in efficiency measurement.However,the existing literature on data envelopment analysis(DEA)in environmental factors ignores the impact of demand on output.To address this gap,we propose the Point-wise Minimization DEA model(PWMDEA),which considers contextual variables that affect demand and lead to differences in efficiency.The model obtains efficiency value by considering the minimum of virtual inputs and virtual demand.Then,efficiency is evaluated by minimizing the ratio of above minimum to virtual output.This one-step model avoids issues of multi-stage assumptions and requires less data,making it more applicable.Moreover,we demonstrate the accuracy of our new model by conducting simulations with given true efficiency values.The simulation results demonstrate that our model has the lowest ranking error when the output is affected by multiple inputs or when demand has a significant impact.In addition,we evaluate the efficiency of healthcare in 31 Chinese provinces by considering two environmental factors.The results suggest that provinces with lower financial investments or population loss received higher rankings from our proposed model.These findings provide plausible explanations and demonstrate the practical usefulness of our model.展开更多
This paper proposes a new approach for stock efficiency evaluation based on multiple risk measures. A derived programming model with quadratic constraints is developed based on the envelopment form of data envelopment...This paper proposes a new approach for stock efficiency evaluation based on multiple risk measures. A derived programming model with quadratic constraints is developed based on the envelopment form of data envelopment analysis(DEA). The derived model serves as an input-oriented DEA model by minimizing inputs such as multiple risk measures. In addition, the Russell input measure is introduced and the corresponding efficiency results are evaluated. The findings show that stock efficiency evaluation under the new framework is also effective. The efficiency values indicate that the portfolio frontier under the new framework is more externally enveloped than the DEA efficient surface under the standard DEA framework.展开更多
文摘This paper proposes a new approach for ranking efficiency units in data envelopment analysis as a modification of the super-efficiency models developed by Tone [1]. The new approach based on slacks-based measure of efficiency (SBM) for dealing with objective function used to classify all of the decision-making units allows the ranking of all inefficient DMUs and overcomes the disadvantages of infeasibility. This method also is applied to rank super-efficient scores for the sample of 145 agricultural bank branches in Viet Nam during 2007-2010. We then compare the estimated results from the new SCI model and the exsisting SBM model by using some statistical tests.
文摘The aim of the paper is to benchmark the performance of the Indian fertilizermanufacturing organizations based on the ranking of efficiencies using a fuzzy data envelopment analysis(FDEA).FDEA has been used to find the relative efficiency and ranking of the fertilizer-manufacturing organizations.The last few years’data have been converted into the fuzzy inputs and outputs as minimum,mean,and maximum values,respectively.The performance of the fertilizer manufacturing organizations is based on the output maximization model of DEA.The frontier organizations set the benchmark for the lagging organizations for further improvement in the performance.This method can also be used to incorporate the data of the several years for multiple inputs and outputs instead of consideration of data of only one year.The proposed approach in this study may help organizations to improve its efficiency to fulfill its goal.
基金supported by grants from the National Science Foundation of China[Grants 72122013,72221001 and 71801151].
文摘Environmental variables are widely recognized as a cause of differences in efficiency measurement.However,the existing literature on data envelopment analysis(DEA)in environmental factors ignores the impact of demand on output.To address this gap,we propose the Point-wise Minimization DEA model(PWMDEA),which considers contextual variables that affect demand and lead to differences in efficiency.The model obtains efficiency value by considering the minimum of virtual inputs and virtual demand.Then,efficiency is evaluated by minimizing the ratio of above minimum to virtual output.This one-step model avoids issues of multi-stage assumptions and requires less data,making it more applicable.Moreover,we demonstrate the accuracy of our new model by conducting simulations with given true efficiency values.The simulation results demonstrate that our model has the lowest ranking error when the output is affected by multiple inputs or when demand has a significant impact.In addition,we evaluate the efficiency of healthcare in 31 Chinese provinces by considering two environmental factors.The results suggest that provinces with lower financial investments or population loss received higher rankings from our proposed model.These findings provide plausible explanations and demonstrate the practical usefulness of our model.
基金supported by the National Natural Science Foundation of China under Grant Nos.72071192,71671172the Anhui Provincial Quality Engineering Teaching and Research Project Under Grant No.2020jyxm2279+2 种基金the Anhui University and Enterprise Cooperation Practice Education Base Project under Grant No.2019sjjd02Teaching and Research Project of USTC(2019xjyxm019,2020ycjg08)the Fundamental Research Funds for the Central Universities(WK2040000027)。
文摘This paper proposes a new approach for stock efficiency evaluation based on multiple risk measures. A derived programming model with quadratic constraints is developed based on the envelopment form of data envelopment analysis(DEA). The derived model serves as an input-oriented DEA model by minimizing inputs such as multiple risk measures. In addition, the Russell input measure is introduced and the corresponding efficiency results are evaluated. The findings show that stock efficiency evaluation under the new framework is also effective. The efficiency values indicate that the portfolio frontier under the new framework is more externally enveloped than the DEA efficient surface under the standard DEA framework.
