Efficiency Evaluation of Economic Enterprise in Presence of Interval Undesirable and Negative Data
محورهای موضوعی : Operation ResearchMahnaz Maghbouli 1 , Mahdi Eini 2 , Farhad Taher 3 , Fatemeh Ghomanjani 4
1 - هیات علمی گروه ریاضی، دانشگاه آزاد اسلامی واحد ارس، جلفا، ایران.
2 - هیات علمی
3 - دانشگاه آزاد اسلامی، واحد تبریز، گروه ریاضی کاربردی
4 - موسسه آموزش عالی کاشمر، کاشمر، ایران
کلید واژه: Data Envelopment Analysis (DEA), Negative data, Efficiency, Interval data, Undesirable outputs,
چکیده مقاله :
Data envelopment analysis (DEA) as a non-parametric method has covered a wide range of applications in measuring comparative efficiency of decision making units (DMUs) with multiple incommensurate inputs and outputs. The standard DEA method requires that all input and output variables be known as semi positive. In many real situations, the presence of undesirable and even negative data are inevitable. In DEA literature there have been various approaches to enable DEA to deal with negative data. On the other hand, the structure of interval data has recently attracted considerable attention among DEA researchers. According to importance of interval data, this paper proposes a radial measure which permits the presence of undesirable and negative data with interval structure. The proposed model can evaluate the efficiency of all DMUs and leads to improve the inefficient unit with interval negative and undesirable data. To elucidate the details of the proposed method an illustrative example of a private bank in IRAN explores the applicability of the proposed method.
Data envelopment analysis (DEA) as a non-parametric method has covered a wide range of applications in measuring comparative efficiency of decision making units (DMUs) with multiple incommensurate inputs and outputs. The standard DEA method requires that all input and output variables be known as semi positive. In many real situations, the presence of undesirable and even negative data are inevitable. In DEA literature there have been various approaches to enable DEA to deal with negative data. On the other hand, the structure of interval data has recently attracted considerable attention among DEA researchers. According to importance of interval data, this paper proposes a radial measure which permits the presence of undesirable and negative data with interval structure. The proposed model can evaluate the efficiency of all DMUs and leads to improve the inefficient unit with interval negative and undesirable data. To elucidate the details of the proposed method an illustrative example of a private bank in IRAN explores the applicability of the proposed method.
