A generalized inverse DEA model for firm restructuring based on value efficiency

We present a novel general inverse data envelopment analysis model for assessing the restructuring of decision-making units (DMUs) while observing predetermined value efficiency targets, under two distinct scenarios: merger and acquisitions and split. By considering the set of efficient DMUs as the Decision Maker's set of Most Preferred Solutions, virtual new units with desired targets for value efficiency scores and input and output levels can be computed. The innovations of this paper are threefold. First, a comparison between the proposed value efficiency and previous technical efficiency approaches reveals improvement in the estimation of restructured input/output levels. Second, the proposed approach is capable of handling the decision-maker's preferences during restructuring. Third, an algorithm to determine the worst case-scenario for restructuring is presented. An applied case study in banking operations is presented to illustrate the validity and applicability of the proposed method.

Automated summary

In this paper, a novel general inverse data envelopment analysis model is presented for evaluating the restructuring of decision-making units. The proposed model shows improvements in estimating the input/output levels, handles decision-maker's preferences, and provides an algorithm for determining the worst case-scenario in restructuring.