摘要
In the traditional data envelopment analysis （DEA） structure, the efficiency score for one decision making unit （DMU） is calculated by measuring the distance of the evaluated DMU to the best practice frontier. Recent researches have provided the reasonability of considering the worst practice frontier as a supple- ment to the traditional DEA techniques. The existing researches take only one type of frontier into account, and they cannot com- pare the evaluated DMU with both the best and the worst perform- ing DMUs. A DEA-based procedure is developed to consider the best and the worst frontiers in the same scenario where the ratio of two distances （RDS） measure is proposed. The principal appli- cation of this approach is for ranking, and, as a complement tool, for performance evaluation. The proposed approach can be used in a wide range of applications such as the performance evaluation of employees and others. Finally, a bookstore data set is used to illustrate the proposed approach.
In the traditional data envelopment analysis （DEA） structure, the efficiency score for one decision making unit （DMU） is calculated by measuring the distance of the evaluated DMU to the best practice frontier. Recent researches have provided the reasonability of considering the worst practice frontier as a supple- ment to the traditional DEA techniques. The existing researches take only one type of frontier into account, and they cannot com- pare the evaluated DMU with both the best and the worst perform- ing DMUs. A DEA-based procedure is developed to consider the best and the worst frontiers in the same scenario where the ratio of two distances （RDS） measure is proposed. The principal appli- cation of this approach is for ranking, and, as a complement tool, for performance evaluation. The proposed approach can be used in a wide range of applications such as the performance evaluation of employees and others. Finally, a bookstore data set is used to illustrate the proposed approach.
基金
supported by the National Natural Science Foundation of China(71121061
71271195
71322101)
the National Social Science Fund of China(13CTQ042)
the USTC Foundation for Innovative Research Team(WK2040160008)
作者简介
Yang Feng was born in 1977. He received his Ph.D. degree in management science and engineer- ing from University of Science and Technology of China in 2006. Afterwards, he worked in Schulich School of Business York University in Canada as a visiting scholar. He returned to University of Sci- ence and Technology of China in 2007. He is a professor in School of Management, University ofScience and Technology of China. He has published more than 30 ar- ticles in a wide range of international academic journals. His research interests include data envelopment analysis and multi-criteria decision modeling. E-mail： fengyang@ustc.edu.cnFei Du was born in 1987. She is a Ph.D. candidate in School of Management, University of Science and Technology of China. She has published several SCI or SSCI indexed articles in international aca- demic journals. Her research interests are data en- velopment analysis and supply chain management. E-mail： dufei @ mail.ustc.edu.cnLiang Liang was born in 1962. He received his Ph.D. degree in System Engineering from South- east University. He is a professor in School of Man- agement, University of Science and Technology of China. He is also the vice president of Hefei Uni- versity of technology, He is also a guest editor of International Journal of Mass Customization, and Asian-Pacific Business Reviews. He was the exec-utive Dean of School of Management University of Science and Technol- ogy of China from 2003 to 2013. He has published more than 100 articles in a wide range of international academic journals. His research interests include supply chain management and data envelopment analysis. E-mail： lliang@ustc.edu.cnLiuyi Ling was born in 1969. He obtained his Ph.D. degree in management science and engineering from University of Science and Technology of China in 2006. He is a lecturer in School of Management. University of Science and Technology of China. He has published more than 10 articles in a wide range of international academic journals. His research in- terests are supply chain management and decision modeling. E-mail： lyling@ustc.edu.cn
