A risk averse cross-efficiency data envelopment analysis model for sustainable switchgrass cultivation location optimization

Environmental concerns and energy security have led to growing interest to second-generation biofuel production from non-edible feedstock such as switchgrass. In this article, sustainable and ecological indicators are introduced to evaluate the candidate locations efficiency for switchgrass cultivation. To optimize the candidate locations, a novel data envelopment analysis (DEA) cross-efficiency model is proposed which attempts to maximize output worst-cases of all candidate locations. Moreover, in order to consider both mean and standard deviation of candidate locations cross-efficiencies, a new ranking measure is presented. The performance of proposed model is investigated in comparison with several models through a real case study in Iran. The efficiency values of Iran provinces are calculated by several DEA cross-efficiency models. The numerical results show that proposed model manages to evaluate the candidate locations efficiency more moderate than other models. Besides, the standard deviation of cross-efficiencies for this model are lower than that of other models. The obtained findings from introduced DEA model reveal that based on the defined ranking measures, Khouzesan and Fars provinces are non-dominate locations for switchgrass cultivation.