The technique for efficiency measurement known as Data Envelopment Analysis (DEA) has been extended to allow on-discretionary inputs that affect production. Several methods exist for measuring efficiency to control these factors in production. This paper review these approaches, providing a discussion of strengths and weaknesses and highlighting potential limitations. In addition, a new approach is developed that overcomes existing weaknesses and it is based on relative importance. To facilitate comparison, a numerical example is used. The results show that the new approach improve existing models and performs relatively well.
Fallah Jelodar, M. (2018). A method to consider Non-Discretionary factors in Data Envelopment Analysis. Caspian Journal of Mathematical Sciences, 7(2), 113-121. doi: 10.22080/cjms.2018.9820.1277
MLA
Mehdi Fallah Jelodar. "A method to consider Non-Discretionary factors in Data Envelopment Analysis", Caspian Journal of Mathematical Sciences, 7, 2, 2018, 113-121. doi: 10.22080/cjms.2018.9820.1277
HARVARD
Fallah Jelodar, M. (2018). 'A method to consider Non-Discretionary factors in Data Envelopment Analysis', Caspian Journal of Mathematical Sciences, 7(2), pp. 113-121. doi: 10.22080/cjms.2018.9820.1277
VANCOUVER
Fallah Jelodar, M. A method to consider Non-Discretionary factors in Data Envelopment Analysis. Caspian Journal of Mathematical Sciences, 2018; 7(2): 113-121. doi: 10.22080/cjms.2018.9820.1277
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