Abstract
This paper describes an application of data envelopment analysis (DEA) to the performance assessment of Portuguese bank branches. The analysis shows how DEA can complement the profitability measure currently used at the bank. The use of an efficiency-profitability matrix enabled the characterisation of the branches' performance profile. Consistent with the bank's development objectives, the analysis focused on the relation between branch size and performance. Two alternative target setting strategies were explored. One eliminates pure technical inefficiencies by focusing on the selection of appropriate benchmarks. The other attains the branches' most productive scale size through the elimination of scale inefficiencies, with minimal changes to branches' scale size.

Abstract
This paper explores the evolution of productivity of the artisanal dredge fleet that operates in the south coast of Portugal. This fleet is considered to be one of the most significant in the sector, essentially due to the volume and value of its catches. In this context, the study carried out sought in first place to determine variation in productivity over a time window of 10 years (between 1995 and 2004). Secondly, it sought to distinguish the performance of local and coastal vessels comprising the chosen fleet, The performance of the five homeports in the Algarve coast was also compared. We used Malmquist indexes to measure productivity change and explored the impact of changes in stock conditions and in regulatory policies on productivity levels. During the time period analysed, the measures defined by regulatory entities included allowing the use of a new type of dredge and the establishment of fishing quotas per vessel and per species. Finally, the fishing quotas allowed for each vessel were confronted with the captures officially declared.

Abstract
Oliveira, M. M., Camanho, A. S., and Gaspar, M. B. 2010. Technical and economic efficiency analysis of the Portuguese artisanal dredge fleet. - ICES Journal of Marine Science, 67: 1811-1821. An efficiency analysis of the commercial dredge fleet operating along the south coast of Portugal between 2005 and 2007 sought to determine the efficiency of the vessels using data envelopment analysis models, considering fixed inputs (vessel power, length, tonnage, and an indicator of stock biomass) and a variable input (number of days at sea). The annual quota per vessel was also included in the model as a contextual factor. In the technical-efficiency (TE) analysis, outputs were defined by the catch weight for each of the three target species (bivalves). Using price data for each species in the wholesale market, revenue efficiency was also estimated to complement the TE analysis. The advantage of the approach lies in the ability to separate technical aspects from allocative aspects in the efficiency assessment, allowing two-dimensional graphic representation of vessel performance. The procedure allows the identification of benchmark vessels, which maximized the catch weight of the species landed, given their inputs, as well as the vessels that selected the appropriate target species to maximize the revenue of the fishing activity, given output prices. The approach also allowed the specification of targets for inefficient vessels that correspond to the catch by species, permitting revenue maximization from fishing.

Abstract
This study develops a framework that combines different management science methods to provide insights concerning the performance of retailing stores. First, the framework enables to specify appropriate targets for stores of a retail network using data envelopment analysis. This involves comparing stores within homogenous groups, that is, supermarkets and hypermarkets. Second, the framework compares the overall performance of these two groups. This requires the combined use of a Malmquist-type index and statistical tests. This index is decomposed into sub-indices for comparing the differences between groups in terms of the efficiency spread in each group of stores and the productivity differences between the best-practice frontiers spanned by the benchmark stores from each group. The hypothesis tests are used to verify if the differences between groups captured by the sub-indices are statistically significant. Journal of the Operational Research Society (2012) 63, 631-645. doi:10.1057/jors.2011.63 Published online 13 July 2011

Abstract
This paper develops a method based on data envelopment analysis (DEA) for efficiency assessments taking into account the effect of non-discretionary factors. A typology that classifies the non-discretionary factors into two groups is proposed: the factors that characterize the external conditions where the decision making units (DMUs) operate (external factors), and the factors that are internal to the production process but cannot be controlled by the decision makers (internal factors). This paper proposes an enhanced DEA model that accommodates non-discretionary inputs and outputs and treats them differently depending on their classification as internal or external to the production process. This generalized model integrates the previous approaches for dealing with non-discretionary variables described in the DEA literature. The model defines the efficient frontier based exclusively on the discretionary variables and internal non-discretionary factors, but the potential peers of each DMU are restricted to other units facing comparable external conditions (represented by the external non-discretionary factors). The peer selection criteria implemented in the DEA model is informed by decision makers' opinion, The applicability of the model developed is illustrated with a real-world assessment of retailing stores.

Abstract
This paper describes a method for the assessment of retail store performance based on Data Envelopment Analysis (DEA). The assessment considers the stores as complex organizations that aggregate several subunits, corresponding to sections with management autonomy. This structure motivated an analysis at two different levels: the section level and the store level. The performance assessment of the sections envolves a comparison among similar sections located in different stores, and evaluates efficiency spread. This is followed by an analysis at the store level to define targets for the sections. This analysis takes into account the interdependencies of the sections composing a store, as they share limited resources such as the floor area. This is achieved using a Network DEA model, which determines the maximum store sales allowing for reallocations of area among the sections within a store. The method developed is illustrated using a case study consisting of a Portuguese chain of supermarkets.