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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.

Keywords:

Data Envelopment Analysis , Efficiency , Non-discretionary Factors