ABSTRACT
Mergers and acquisitions (M&As) are strategic decisions that enable consolidation of multiple firms in order to expand market share, gain access to new markets and enhance production capabilities. In this paper, we show that farms’ mergers, as opposed to individual farms, can have a sizable contribution to sustainability. Using Inverse data envelopment analysis (InvDEA) as a methodological framework, we investigate the impact of mergers on enhancing sustainability in the agricultural production sector through optimizing energy requirements. The investigations are carried out on a sample of 15 cucumber GH farms in the Batinah region of Oman, Based on the data analysis, electricity and fertilizers emerged as major energy inputs, utilizing 81.84% and 15.61% of the total energy inputs, respectively. The application of the standard DEA model produced an average technical efficiency of 0.9635 with 80% of the GH farms declared efficient. The next major part of the study consists of implementing the inverse DEA approach to 435 pairwise consolidations of the GH farms, where only 18 mergers were identified as productive. In spite of the high level of efficiency among the GH farms, the results revealed that 50% of the productive post-merger GH farms comprise exclusively efficient GH farm, that is, energy savings are still conceivable even if the merging farms are seemingly efficient. The analysis of the energy outcomes indicated that the average proportions of potential energy gains per post-merger GH farm fall between 19.58% and 55.64%, with the highest figures reported for electricity. The post-mergers’ energy savings for labor, machinery, fertilizers, chemicals, water and electricity reached proportions as high as 82.22%, 68.22%, 84.73%, 51.15%, 76.41% and 82.07%, respectively. Additionally, a synergy merge index (SMI) is developed to optimally pair GH farms. The selected plan contributed to improving the energy savings by a factor of more than 4, where the share of electricity represents alone 91.05%, followed by 7.88% for fertilizers. The application scope of the proposed methodology can be extended to other sectors where energy consumption might be a critical issue.
