An inverse network DEA model for two-stage processes in the presence of undesirable factors

The inverse data envelopment analysis (DEA) problem is one of the noticeable issues in the recent decades. The inverse DEA allows a manager to increase (or decrease) outputs (or inputs) of units under evaluation and determine the amount of changes of inputs or outputs, so that the level of efficiency of the mentioned units is preserved. Note that in the real word, many processes have a network structure. So, in this paper, we introduce an inverse network DEA for a two-stage network structure in the presence of undesirable factors. The weak disposability assumption is used to handle undesirable outputs. The advantage of the proposed method is that it can increase and decrease outputs (or inputs) simultaneously. To illustrate the new model, a real application on some poultry farms is used.