Investigating prospective gains from mergers in the agricultural sector through Inverse DEA

Abstract

Abstract This paper presents a new application of Inverse data envelopment analysis (InvDEA) for strategic decision making: mergers & acquisitions (M&A) in the agricultural sector. Given a set of agricultural farms, the decision maker is interested in estimating the potential gains that are likely to result from the merger of two or more farms, as well as the redistribution of inputs among the merging farms, for an efficiency target set a priori for the post-merger farm. Using a sample of greenhouse (GH) farms from the Batinah region (Oman), an InvDEA approach is applied to investigate pairwise consolidations among GH farms and determine the level of inputs required for a merger to achieve full efficiency. Moreover, a DEA-based approach is introduced for selecting the best partners of a merger based on pertaining potential gains. The results highlight the importance of mergers as a strategic option for an efficient management of resources in the agricultural sector, especially scarce resources, like water and electricity.