A bi-level multi-objective data envelopment analysis model for estimating profit and operational efficiency of bank branches

Data Envelopment Analysis (DEA) is a powerful method for analyzing the performance of decision making units
(DMUs). Traditionally, DEA is applied for estimating the performance of a set of DMUs through measuring a single
perspective of efficiency. However, in recent years, due to increasing competition in various industries, modern
enterprises focus on enhancing their performance by measuring efficiencies in different aspects, separately or
simultaneously. This paper proposes a bi-level multi-objective DEA (BLMO DEA) model which is able to assess
the performance of DMUs in two different hierarchical dimensions, simultaneously. In the proposed model, we
define two level efficiency scores for each DMU. The aim is to maximize these two efficiencies, simultaneously, for
each DMU. Since the objective functions at both levels are fractional, a fuzzy fractional goal programming (FGP)
methodology is used to solve the proposed BLMO DEA model. The capability of the proposed model is illustrated
by a numerical example. Finally, to practically validate the proposed model, a real case study from 45 bank’s
branches is applied. The results show that the proposed model can provide a more comprehensive measure for
efficiency of each bank’s branch based on simultaneous measuring of two different efficiencies, profit and
operational efficiencies, and by considering the level of their importance.