Inverse DEA and inverse DEA cost efficiency models for mergers: Some theoretical issues

Abstract

Over the last few decades, Merger and Acquisitions (M&A) have been considered as powerful strategies for managers of production units, in order to improve the efficiency, expand market share, and enhance their production capabilities. Especially, it has been verified that the Inverse Data Envelopment Analysis (InvDEA) approach can be successfully implemented in this field, with the aim of estimating the required level of inputs and/or outputs of the merged units that realizes an efficiency target. In this paper, we investigate some of the existing InvDEA approaches for mergers in details, and present some developments.