Using inverse data envelopment analysis to evaluate potential impact of mergers on energy use optimization - Application in the agricultural production

This paper examines the potential of Mergers & Acquisitions (M&As) as a novel approach to energy use optimization. The investigations are carried out through inverse data envelopment analysis (DEA). Contrary to traditional DEA approaches that restrict the energy savings to individual production units, the proposed methodology looks at the issue from the perspective of possible mergers among these units. The new methodology, which deploys over two stages, is applied to pairwise consolidations among 51 tomato greenhouse (GH) farms from Biskra, Algeria. An inverse DEA model is implemented in the first stage to discern all possibly productive post-merger GH farms, i.e., those mergers that are likely to generate energy gains. In the second stage, a new procedure is devised to find the best matchings among partners of potential mergers and derive the best merger plan out of the whole sample of GH farms. The results of the inverse DEA application revealed that potential gains per energy input can be substantial, reaching proportions as high as 80.78% and above. The derived optimal merger plan exhibited a post-merger energy saving index of 70.23%, that is, 33 times the index of the traditional DEA approach. Practically, these findings leave no doubt that mergers can contribute significantly to energy savings, enough to support new policies for promoting mergers as strategic options towards optimal energy consumption. The application scope of the proposed methodology can be duly extended to other sectors where energy optimization might be a critical issue.