Group efficiency analysis in decision processes: a data envelopment analysis approach

Data envelopment analysis (DEA) is a powerful mathematical programming methodology for evaluating the relative efficiency of decision-making units (DMUs) with multiple outputs and multiple inputs. In the classic DEA, it has been implicitly assumed that all DMUs perform in a unique technology set and the traditional DEA cannot measure the relative performances of DMUs with dissimilar classes. In other words, if we have different groups of DMUs, the traditional DEA models cannot be applied to evaluate such cases. In this paper, it has been assumed that the DMUs do business in different groups. We are interested to evaluate the members of the groups. The main aim of this paper is proposing a DEA-based methodology to estimate the technical efficiency of DMUs along with different groups with different technologies. The proposed method is illustrated by an empirical example on banking industry.